Shun'ichi Amari | Academic Influence

Shun'ichi Amari's AcademicInfluence.com Rankings

Shun'ichi Amari

Engineering

#205

World Rank

#390

Historical Rank

Electrical Engineering

#119

World Rank

#136

Historical Rank

engineering Degrees

Shun'ichi Amari

Mathematics

#404

World Rank

#820

Historical Rank

Measure Theory

#116

World Rank

#186

Historical Rank

mathematics Degrees

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Engineering
Mathematics

Shun'ichi Amari's Degrees

PhD Mathematical Engineering University of Tokyo

Why Is Shun'ichi Amari Influential?

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According to Wikipedia, Shun'ichi Amari, is a Japanese scholar born in 1936 in Tokyo, Japan. Overviews He majored in Mathematical Engineering in 1958 from the University of Tokyo then graduated in 1963 from the Graduate School of the University of Tokyo.

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Shun'ichi Amari's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Natural Gradient Works Efficiently in Learning (1998) (2909)
Methods of information geometry (2000) (2520)
A New Learning Algorithm for Blind Signal Separation (1995) (2256)
Nonnegative Matrix and Tensor Factorizations - Applications to Exploratory Multi-way Data Analysis and Blind Source Separation (2009) (2184)
Dynamics of pattern formation in lateral-inhibition type neural fields (1977) (1744)
Adaptive Blind Signal and Image Processing - Learning Algorithms and Applications (2002) (1625)
Differential-geometrical methods in statistics (1985) (1546)
Adaptive blind signal and image processing (2002) (1479)
Improving support vector machine classifiers by modifying kernel functions (1999) (901)
Network information criterion-determining the number of hidden units for an artificial neural network model (1994) (675)
Adaptive blind signal processing-neural network approaches (1998) (538)
A Theory of Pattern Recognition (1968) (474)
A Theory of Adaptive Pattern Classifiers (1967) (468)
Families of Alpha- Beta- and Gamma- Divergences: Flexible and Robust Measures of Similarities (2010) (449)
Information geometry on hierarchy of probability distributions (2001) (416)
Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements (1972) (390)
Information Geometry and Its Applications (2016) (390)
Statistical neurodynamics of associative memory (1988) (387)
Differential Geometry of Curved Exponential Families-Curvatures and Information Loss (1982) (378)
Adaptive Online Learning Algorithms for Blind Separation: Maximum Entropy and Minimum Mutual Information (1997) (374)
Multichannel blind deconvolution and equalization using the natural gradient (1997) (372)
Asymptotic statistical theory of overtraining and cross-validation (1997) (358)
Information geometry of the EM and em algorithms for neural networks (1995) (353)
Underdetermined blind source separation based on sparse representation (2006) (330)
Interpolating between Optimal Transport and MMD using Sinkhorn Divergences (2018) (320)
Csiszár's Divergences for Non-negative Matrix Factorization: Family of New Algorithms (2006) (318)
Analysis of Sparse Representation and Blind Source Separation (2004) (317)
Stability Analysis of Learning Algorithms for Blind Source Separation (1997) (305)
Blind source separation-semiparametric statistical approach (1997) (289)
Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization (2007) (284)
Backpropagation and stochastic gradient descent method (1993) (279)
Competition and Cooperation in Neural Nets (1982) (262)
Neural theory of association and concept-formation (1977) (257)
New Algorithms for Non-Negative Matrix Factorization in Applications to Blind Source Separation (2006) (242)
Mathematical foundations of neurocomputing (1990) (240)
Information geometry (2021) (228)
Flexible Independent Component Analysis (1998) (222)
Information geometry of Boltzmann machines (1992) (219)
Generalized Alpha-Beta Divergences and Their Application to Robust Nonnegative Matrix Factorization (2011) (213)
Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons (2000) (210)
Characteristics of sparsely encoded associative memory (1989) (207)
Neural Learning in Structured Parameter Spaces - Natural Riemannian Gradient (1996) (204)
Natural Gradient Learning for Over- and Under-Complete Bases in ICA (1999) (194)
Local minima and plateaus in hierarchical structures of multilayer perceptrons (2000) (191)
Topographic organization of nerve fields (1979) (187)
Statistical Inference Under Multiterminal Data Compression (1998) (176)
Adaptive natural gradient learning algorithms for various stochastic models (2000) (174)
Information-theoretic approach to blind separation of sources in non-linear mixture (1998) (173)
Why natural gradient? (1998) (167)
Bayesian Robust Tensor Factorization for Incomplete Multiway Data (2014) (167)
Measuring Integrated Information from the Decoding Perspective (2015) (166)
$\alpha$ -Divergence Is Unique, Belonging to Both $f$-Divergence and Bregman Divergence Classes (2009) (166)
Field theory of self-organizing neural nets (1983) (164)
Identifiability of hidden Markov information sources and their minimum degrees of freedom (1992) (160)
Information geometry of divergence functions (2010) (157)
Information-Geometric Measure for Neural Spikes (2002) (156)
Existence and stability of local excitations in homogeneous neural fields (1979) (153)
Four Types of Learning Curves (1992) (146)
Statistical Theory of Learning Curves under Entropic Loss Criterion (1993) (143)
Population Coding and Decoding in a Neural Field: A Computational Study (2002) (142)
Nonnegative Matrix and Tensor Factorization [Lecture Notes] (2008) (141)
Sequential blind signal extraction in order specified by stochastic properties (1997) (131)
Capacity of associative memory using a nonmonotonic neuron model (1993) (130)
Stability of asymmetric Hopfield networks (2001) (129)
The AIC Criterion and Symmetrizing the Kullback–Leibler Divergence (2007) (126)
Synchronous Firing and Higher-Order Interactions in Neuron Pool (2003) (125)
Integration of Stochastic Models by Minimizing -Divergence (2007) (119)
Extended SMART Algorithms for Non-negative Matrix Factorization (2006) (118)
Homogeneous nets of neuron-like elements (1975) (118)
A self-stabilized minor subspace rule (1998) (116)
Stability Analysis Of Adaptive Blind Source Separation (1997) (116)
From blind signal extraction to blind instantaneous signal separation: criteria, algorithms, and stability (2004) (114)
Differential geometry of statistical inference (1983) (112)
Singularities Affect Dynamics of Learning in Neuromanifolds (2006) (111)
Novel On-Line Adaptive Learning Algorithms for Blind Deconvolution Using the Natural Gradient Approach (1997) (111)
Sensori-motor transformations in the brain (with a critique of the tensor theory of cerebellum). (1985) (111)
State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data (2012) (111)
Unified framework for information integration based on information geometry (2015) (110)
Nonholonomic Orthogonal Learning Algorithms for Blind Source Separation (2000) (106)
Brain-like Computing and Intelligent Information Systems (1998) (106)
SPARSE COMPONENT ANALYSIS FOR BLIND SOURCE SEPARATION WITH LESS SENSORS THAN SOURCES (2003) (105)
Conformal Transformation of Kernel Functions: A Data-Dependent Way to Improve Support Vector Machine Classifiers (2002) (104)
Universal statistics of Fisher information in deep neural networks: mean field approach (2018) (103)
Non-Negative Tensor Factorization using Alpha and Beta Divergences (2007) (99)
Shape Retrieval Using Hierarchical Total Bregman Soft Clustering (2012) (98)
Dynamic Interactions in Neural Networks: Models and Data (1988) (98)
A unified algorithm for principal and minor components extraction (1998) (97)
Information geometry of estimating functions in semi-parametric statistical models (1997) (97)
Total Bregman Divergence and Its Applications to DTI Analysis (2011) (97)
A Mathematical Foundation for Statistical Neurodynamics (1977) (96)
A universal theorem on learning curves (1993) (94)
Natural Gradient Works Eciently in Learning (93)
Neuroinformatics: the integration of shared databases and tools towards integrative neuroscience. (2002) (92)
Recurrent Neural Networks For Blind Separation of Sources (1995) (90)
Removal of ballistocardiogram artifacts from simultaneously recorded EEG and fMRI data using independent component analysis (2006) (89)
Learned parametric mixture based ICA algorithm (1998) (89)
On gradient adaptation with unit-norm constraints (2000) (88)
Natural gradient descent for on-line learning (1998) (88)
Unified stabilization approach to principal and minor components extraction algorithms (2001) (88)
Adaptive On-line Learning in Changing Environments (1996) (87)
Competitive and Cooperative Aspects in Dynamics of Neural Excitation and Self-Organization (1982) (87)
Population Coding with Correlation and an Unfaithful Model (2001) (86)
A method of statistical neurodynamics (1974) (85)
Robust techniques for independent component analysis (ICA) with noisy data (1998) (84)
Multichannel blind separation and deconvolution of sources with arbitrary distributions (1997) (82)
Geometry of q-Exponential Family of Probability Distributions (2011) (79)
Dynamics and Computation of Continuous Attractors (2008) (79)
Information geometry of turbo and low-density parity-check codes (2004) (78)
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective? (1995) (77)
Dualistic differential geometry of positive definite matrices and its applications to related problems (1996) (77)
New theorems on global convergence of some dynamical systems (2001) (75)
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering (2007) (75)
Stochastic Reasoning, Free Energy, and Information Geometry (2004) (74)
Natural gradient algorithm for blind separation of overdetermined mixture with additive noise (1999) (74)
Dynamics of Learning Near Singularities in Layered Networks (2008) (71)
A robust approach to independent component analysis of signals with high-level noise measurements (2003) (71)
Dualistic geometry of the manifold of higher-order neurons (1991) (71)
Error bound of hypothesis testing with data compression (1994) (69)
Information geometry connecting Wasserstein distance and Kullback–Leibler divergence via the entropy-relaxed transportation problem (2017) (68)
Statistical inference under multiterminal rate restrictions: A differential geometric approach (1989) (68)
Geometrical theory of asymptotic ancillarity and conditional inference (1982) (67)
On-line learning in changing environments with applications in supervised and unsupervised learning (2002) (66)
Sparse Representation for Brain Signal Processing: A tutorial on methods and applications (2014) (66)
Estimating Spiking Irregularities Under Changing Environments (2006) (65)
Asymptotic Theory of Estimation (1985) (64)
Self-adaptive blind source separation based on activation functions adaptation (2004) (64)
Geometry of deformed exponential families: Invariant, dually-flat and conformal geometries (2012) (62)
Gradient systems in view of information geometry (1995) (60)
Complexity Issues in Natural Gradient Descent Method for Training Multilayer Perceptrons (1998) (60)
Computing with Continuous Attractors: Stability and Online Aspects (2005) (58)
A common neural-network model for unsupervised exploratory data analysis and independent component analysis (1998) (58)
Chapter 4: Statistical Manifolds (1987) (58)
Formation of topographic maps and columnar microstructures in nerve fields (1979) (58)
Differential geometry of a parametric family of invertible linear systems—Riemannian metric, dual affine connections, and divergence (1987) (57)
A Numerical Study on Learning Curves in Stochastic Multilayer Feedforward Networks (1996) (56)
Learning Coefficients of Layered Models When the True Distribution Mismatches the Singularities (2003) (56)
Independent component analysis by the information-theoretic approach with mixture of densities (1997) (55)
On Conformal Divergences and Their Population Minimizers (2013) (53)
A Novel Approach to Canonical Divergences within Information Geometry (2015) (53)
Total Bregman divergence and its applications to shape retrieval (2010) (53)
Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints (2007) (53)
Blind estimation of channel parameters and source components for EEG signals: a sparse factorization approach (2006) (52)
Log-Determinant Divergences Revisited: Alpha-Beta and Gamma Log-Det Divergences (2014) (52)
Neuroscience data and tool sharing (2003) (52)
Computational Neuroscience: Mathematical and Statistical Perspectives. (2018) (52)
Equivariant nonstationary source separation (2002) (51)
Dynamical stability of formation of cortical maps (1988) (50)
Independent component analysis for unaveraged single-trial MEG data decomposition and single-dipole source localization (2002) (50)
Superefficiency in blind source separation (1999) (50)
Differential geometry of edgeworth expansions in curved exponential family (1983) (50)
Information Geometry and Its Applications: Convex Function and Dually Flat Manifold (2009) (49)
Blind signal separation and independent component analysis (2002) (48)
Differential and Algebraic Geometry of Multilayer Perceptrons (2001) (48)
Estimating Functions in Semiparametric Statistical Models (1997) (47)
Auto-associative memory with two-stage dynamics of nonmonotonic neurons (1996) (46)
Learning Curves, Model Selection and Complexity of Neural Networks (1992) (45)
Estimating Functions of Independent Component Analysis for Temporally Correlated Signals (2000) (45)
Differential Geometry of Statistical Models (1985) (44)
Dynamics of Learning in Multilayer Perceptrons Near Singularities (2008) (43)
Modeling Basal Ganglia for Understanding Parkinsonian Reaching Movements (2010) (42)
Multichannel blind deconvolution of nonminimum-phase systems using filter decomposition (2004) (41)
Parameter estimation with multiterminal data compression (1995) (41)
Differential geometrical theory of statistics (1987) (40)
Asymptotic theory of sequential estimation : Differential geometrical approach (1991) (40)
On a new blind signal extraction algorithm: different criteria and stability analysis (2002) (40)
Self-whitening algorithms for adaptive equalization and deconvolution (1999) (40)
Geometrical theory of higher-order asymptotics of test, interval estimator and conditional inference (1983) (39)
Statistical analysis of learning dynamics (1999) (39)
Global Exponential Stability of Multitime Scale Competitive Neural Networks With Nonsmooth Functions (2006) (39)
Chapter 3: Differential and Integral Geometry in Statistical Inference (1987) (38)
Identification of Directed Influence: Granger Causality, Kullback-Leibler Divergence, and Complexity (2012) (38)
Dynamics of learning near singularities in radial basis function networks (2008) (38)
Dynamical analysis of contrastive divergence learning: Restricted Boltzmann machines with Gaussian visible units (2016) (38)
Bias removal technique for blind source separation with noisy measurements (1998) (38)
Fisher information for spike-based population decoding. (2006) (36)
Theoretical Study of Oscillator Neurons in Recurrent Neural Networks (2018) (36)
A Cascade Neural Network for Blind Signal Extraction without Spurious Equilibria (1998) (36)
Probability estimation for recoverability analysis of blind source separation based on sparse representation (2006) (35)
Estimation in the Presence of Infinitely many Nuisance Parameters--Geometry of Estimating Functions (1988) (35)
Statistical neurodynamics of various versions of correlation associative memory (1988) (35)
Sparse Representation and Its Applications in Blind Source Separation (2003) (35)
Multi-Layer Neural Networks with a Local Adaptive Learning Rule for Blind Separation of Source Signa (1995) (34)
A Theory ofAdaptive Pattern Classifiers (1967) (33)
A dually flat structure on the space of escort distributions (2010) (33)
The EM Algorithm and Information Geometry in Neural Network Learning (1995) (33)
Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons (2001) (32)
Traveling Bumps and Their Collisions in a Two-Dimensional Neural Field (2011) (32)
A computational study of synaptic mechanisms of partial memory transfer in cerebellar vestibulo-ocular-reflex learning (2008) (32)
Fisher information under restriction of Shannon information in multi-terminal situations (1989) (32)
Difficulty of Singularity in Population Coding (2005) (31)
Mathematical theory on formation of category detecting nerve cells (1978) (31)
Sparsely coded associative memories: capacity and dynamical properties (1991) (31)
Measure of Correlation Orthogonal to Change in Firing Rate (2009) (31)
Information geometry of statistical inference - an overview (2002) (30)
Chapter 2: Differential Geometrical Theory of Statistics (1987) (30)
Information processing in a neuron ensemble with the multiplicative correlation structure (2004) (30)
Combining Classifiers and Learning Mixture-of-Experts (2009) (29)
Network Information Criterion | Determining the Number of Hidden Units for an Articial Neural Network Model Network Information Criterion | Determining the Number of Hidden Units for an Articial Neural Network Model (2007) (29)
On Clustering Histograms with k-Means by Using Mixed α-Divergences (2014) (28)
A Mathematical Approach to Neural Systems (1977) (28)
Equiaffine structures on statistical manifolds and Bayesian statistics (2006) (28)
Chapter 5: Differential Metrics in Probability Spaces (1987) (27)
Neural network approach to blind separation and enhancement of images (1996) (27)
Information Geometry of α-Projection in Mean Field Approximation (2004) (27)
Neuroscience data and tool sharing - A legal and policy framework for neuroinformatics (2003) (26)
Equivalence Probability and Sparsity of Two Sparse Solutions in Sparse Representation (2008) (26)
Learning and statistical inference (1998) (26)
Mutual information of sparsely coded associative memory with self-control and ternary neurons (2000) (26)
Approximate maximum likelihood source separation using the natural gradient (2001) (26)
The Minimum Entropy and Cumulants Based Contrast Functions for Blind Source Extraction (2001) (25)
Multichannel blind deconvolution of non-minimum phase systems using information backpropagation (1999) (24)
Sequential Bayesian Decoding with a Population of Neurons (2003) (24)
Exponential Convergence of Delayed Dynamical Systems (2001) (24)
The Normalization Method for Alleviating Pathological Sharpness in Wide Neural Networks (2019) (24)
Neural Network Models for Blind Separation of Time Delayed and Convolved Signals (1997) (24)
CRITERIA FOR THE SIMULTANEOUS BLIND EXTRACTION OF ARBITRARY GROUPS OF SOURCES (2001) (24)
Dynamics of Learning in MLP: Natural Gradient and Singularity Revisited (2018) (23)
Sequential Extraction of Minor Components (2001) (23)
Curvature of Hessian manifolds (2014) (23)
Information geometry in optimization, machine learning and statistical inference (2010) (23)
An information-geometrical method for improving the performance of support vector machine classifiers (1999) (22)
Natural Gradient Approach To Blind Separation Of Over- And Under-Complete Mixtures (1999) (22)
Differential geometric structures of stable state feedback systems with dual connections (1992) (22)
Unified framework for the entropy production and the stochastic interaction based on information geometry (2018) (22)
Gradient Learning in Structured Parameter Spaces: Adaptive Blind Separation of Signal Sources (1996) (22)
Fisher Information and Natural Gradient Learning of Random Deep Networks (2018) (22)
Gradient adaptation under unit-norm constraints (1998) (22)
Estimation of a structural parameter in the presence of a large number of nuisance parameters (1984) (21)
When Does Preconditioning Help or Hurt Generalization? (2020) (21)
Self-Organization in the Basal Ganglia with Modulation of Reinforcement Signals (2002) (21)
Correlation and Independence in the Neural Code (2006) (21)
State-space analysis on time-varying correlations in parallel spike sequences (2009) (20)
Fast-convergence filtered regressor algorithms for blind equalisation (1996) (20)
Pathological Spectra of the Fisher Information Metric and Its Variants in Deep Neural Networks (2019) (20)
Global Convergence Rate of Recurrently Connected Neural Networks (2002) (20)
A Comparison of Descriptive Models of a Single Spike Train by Information-Geometric Measure (2006) (20)
Convergence of the Wake-Sleep Algorithm (1998) (19)
Information Geometry for Regularized Optimal Transport and Barycenters of Patterns (2019) (19)
/spl alpha/-parallel prior and its properties (2005) (19)
Blind signal extraction using self-adaptive nonlinear Hebbian learning rule (1996) (19)
Adaptive approach to blind source separation with cancellation of additive and convolutional noise (1996) (19)
Attention Modulation of Neural Tuning Through Peak and Base Rate (2001) (19)
Mathematical methods of neurocomputing (1993) (19)
The Efficiency and the Robustness of Natural Gradient Descent Learning Rule (1997) (19)
Information backpropagation for blind separation of sources in nonlinear mixture (1997) (19)
Gene Interaction in DNA Microarray Data Is Decomposed by Information Geometric Measure (2003) (19)
Relationships between instantaneous blind source separation and multichannel blind deconvolution (1998) (19)
Geometrical methods in neural networks and learning (2005) (18)
Semiparametric model and superefficiency in blind deconvolution (2001) (18)
Information Geometry of Positive Measures and Positive-Definite Matrices: Decomposable Dually Flat Structure (2014) (18)
Characteristics of Random Nets of Analog Neuron-Like Elements (1988) (18)
Independent Component Analysis (ICA) and Method of Estimating Functions (2002) (18)
A foundation of information geometry (1983) (18)
Statistical inference: learning in artificial neural networks (1998) (18)
Geometry of Admissible Parameter Region in Neural Learning (1996) (17)
On-line adaptive algorithms in non-stationary environments using a modified conjugate gradient approach (1997) (17)
Equi-convergence Algorithm for Blind Separation of Sources with Arbitrary Distributions (2001) (17)
Mathematical theory of neural learning (1991) (17)
Information Geometry of Neural Networks (2000) (17)
Blind separation of uniformly distributed signals: a general approach (1999) (17)
Single-Trial Magnetoencephalographic Data Decomposition and Localization Based on Independent Component Analysis Approach (2000) (17)
Two Conditions for Equivalence of 0-Norm Solution and 1-Norm Solution in Sparse Representation (2010) (16)
On Optimal Data Compression in Multiterminal Statistical Inference (2011) (16)
Population Decoding Based on an Unfaithful Model (1999) (16)
Local stability analysis of flexible independent component analysis algorithm (2000) (16)
Maximum Likelihood Source Separation: Equivariance and Adaptivity (1997) (16)
Associative Memory and Its Statistical Neurodynamical Analysis (1988) (16)
Information geometry of neural network—an overview (1997) (16)
Dualistic theory of non-Riemannian material manifolds (1981) (16)
Nonlinearity and Separation Capability: Further Justiication for the Ica Algorithm with a Learned Mixture of Parametric Densities (1997) (16)
Improving Generalization Performance of Natural Gradient Learning Using Optimized Regularization by NIC (2004) (16)
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources (2004) (15)
Information-Geometric Measures as Robust Estimators of Connection Strengths and External Inputs (2009) (15)
Effect of initial values in simple perception (1998) (15)
Dreaming of mathematical neuroscience for half a century (2013) (15)
Independent Component Analysis in Multimedia Modeling (2003) (15)
CONFORMAL GEOMETRY OF ESCORT PROBABILITY AND ITS APPLICATIONS (2012) (15)
Discrimination with Spike Times and ISI Distributions (2008) (14)
On Some Extensions Of The Natural Gradient Algorithm (2001) (13)
Information Loss Associated with Imperfect Observation and Mismatched Decoding (2011) (13)
A new discriminant NMF algorithm and its application to the extraction of subtle emotional differences in speech (2012) (13)
Two spatio-temporal decorrelation learning algorithms and their application to multichannel blind deconvolution (1999) (13)
Geometry of Information Integration (2016) (13)
Non-Holonomic Constraints in Learning Blind Source Separation (1997) (12)
Divergence, Optimization and Geometry (2009) (12)
Estimation of Network Parameters in Semiparametric Stochastic Perceptron (1994) (12)
Beyond ICA: robust sparse signal representations (2004) (12)
Information Geometrical Framework for Analyzing Belief Propagation Decoder (2001) (12)
On-line learning in switching and drifting environments with application to blind source separation (1999) (12)
Minkovskian Gradient for Sparse Optimization (2013) (12)
On the capacity of three-layer networks (1990) (12)
Neural Implementation of Bayesian Inference in Population Codes (2001) (12)
Statistical Mechanical Analysis of Online Learning with Weight Normalization in Single Layer Perceptron (2017) (11)
Integration of Stochastic Models by Minimizing alpha-Divergence (2007) (10)
Multi‐Way Array (Tensor) Factorizations and Decompositions (2009) (10)
Alternating Least Squares and Related Algorithms for NMF and SCA Problems (2009) (10)
Statistical mechanical analysis of learning dynamics of two-layer perceptron with multiple output units (2019) (10)
Blind Separation of a Mixture of Uniformly Distributed Source Signals: A Novel Approach (1999) (10)
Any Target Function Exists in a Neighborhood of Any Sufficiently Wide Random Network: A Geometrical Perspective (2020) (9)
Quasi-Newton filtered-error and filtered-regressor algorithms for adaptive equalization and deconvolution (1997) (9)
DIVERGENCE FUNCTION , INFORMATION MONOTONICITY AND INFORMATION GEOMETRY (2009) (9)
Geometrical Structures of FIR Manifold and Multichannel Blind Deconvolution (2002) (9)
Statistical Neurodynamics of Deep Networks: Geometry of Signal Spaces (2018) (9)
Information Geometry on Hierarchical Decomposition of Stochastic Interactions (2007) (9)
Attention modulation of neural tuning through peak and base rate in correlated firing (2002) (9)
Heaviside World: Excitation and Self-Organization of Neural Fields (2014) (9)
Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting (2002) (9)
Information Geometry of Multiple Spike Trains (2010) (9)
Adaptive paraunitary filter banks for principal and minor subspace analysis (1999) (9)
Locally Adaptive Algorithms for ICA and their Implementations (2002) (9)
Learning and inference in hierarchical models with singularities (2003) (9)
Conditional Mixture Model for Correlated Neuronal Spikes (2010) (9)
Sparse Super Symmetric Tensor Factorization (2007) (8)
Information-Geometric Decomposition in Spike Analysis (2001) (8)
Annealed online learning in multilayer neural networks (1999) (8)
Improved Parameter Estimation for Variance-stabilizing Transformation of Gene-expression Microarray Data (2004) (8)
Statistical Analysis of Regularization Constant - From Bayes, MDL and NIC Points of View (1997) (8)
A new learning algorightm for blind signal separation (1996) (8)
Natural Gradient Learning for Spatio-temporal Decorrelation : Recurrent Network (2001) (8)
Representative and Discriminant Feature Extraction Based on NMF for Emotion Recognition in Speech (2009) (8)
Two Gradient Descent Algorithms for Blind Signal Separation (1996) (8)
Representation of higher-order statistical structures in natural scenes via spatial phase distributions (2016) (8)
Robust Bayesian Tensor Factorization for Incomplete Multiway Data (2014) (8)
[Neural Networks: A Review from Statistical Perspective]: Comment (1994) (8)
Can Critical-Point Paths Under ${\ell}_{{p}}$ -Regularization $(0<p<1)$ Reach the Sparsest Least Squares Solutions? (2014) (8)
Nonlinearity and separation capability: further justification for the ICA algorithm with mixture of densities (1997) (7)
Local minima and plateaus in multilayer neural networks (1999) (7)
Training Multi-Layer Perceptrons by Natural Gradient Descent (1997) (7)
State concentration exponent as a measure of quickness in Kauffman-type networks. (2012) (7)
A theory on a neural net with nonmonotone neurons (1993) (7)
$\ell _{p}$ -Regularized Least Squares $(0 and Critical Path (2016) (7)
ℓp-constrained least squares (0 < p < 1) and its critical path (2012) (7)
Introduction – Problem Statements and Models (2009) (7)
<inline-formula> <tex-math notation="LaTeX">$\ell _{p}$ </tex-math></inline-formula>-Regularized Least Squares <inline-formula> <tex-math notation="LaTeX">$(0<p<1)$ </tex-math></inline-formula> and Critical Path (2016) (7)
Training error, generalization error and learning curves in neural learning (1995) (6)
Blind equalization of switching channels by ICA and learning of learning rate (1997) (6)
Asymptotic behaviors of population codes (2002) (6)
Blind source separation with convolutive noise cancellation (1997) (6)
Information Geometry of Wasserstein Divergence (2017) (6)
Special topic section on advances in statistical signal processing for medicine (2000) (6)
Information-Geometrical Significance of Sparsity in Gallager Codes (2001) (6)
Unbiased Estimator of Shape Parameter for Spiking Irregularities under Changing Environments (2005) (6)
A stochastic natural gradient descent algorithm for blind signal separation (1996) (6)
Information Geometry of Neural Networks | New Bayesian Duality Theory | (1996) (6)
Statistical neurodynamics of various types of associative nets (1993) (5)
Adaptive Natural Gradient Learning Algorithms for Unnormalized Statistical Models (2016) (5)
LARGE SCALE SIMULATIONS FOR LEARNING CURVES (5)
Editorial : Special issue on “ Geometrical Methods in Neural Networks and Learning ” (5)
On Extensions of LARS by Information Geometry : Convex Objectives and ' p -Norm (2011) (5)
Multiplicative Iterative Algorithms for NMF with Sparsity Constraints (2009) (5)
Dynamics of Learning In Hierarchical Models – Singularity and Milnor Attractor (2011) (5)
An extended first approximation model for the amygdaloid kindling phenomenon (1978) (5)
Wasserstein statistics in one-dimensional location scale models (2020) (5)
Gradient Adaptive Paraunitary Filter Banks for Spatio-Temporal Subspace Analysis and Multichannel Blind Deconvolution (2004) (5)
Blind Decorrelation and SOS for Robust Blind Identification (2002) (5)
On Some Singularities in Parameter Estimation Problems (2003) (5)
A One-Bit-Matching Learning Algorithm for Independent Component Analysis (2006) (5)
Multiterminal estimation theory with binary symmetric source (1995) (4)
Strategy Under the Unknown Stochastic Environment: the Nonparametric Lob—Pass Problem (1998) (4)
Quasi‐Newton Algorithms for Nonnegative Matrix Factorization (2009) (4)
Information Geometry and Its Applications: Survey (2013) (4)
On different ensembles of kernel machines (2003) (4)
Identifiability of hidden markov processes and their minimum degrees of freedom (1991) (4)
Chapter XIV A Mathematical Theory of Self-Organizing Nerve Systems (1982) (4)
Dynamic interactions in neural networks (1989) (4)
Mathematical theories of neural networks (1997) (4)
Sequential Blind Signal Extraction (2002) (4)
DIFFERENTIAL GEOMETRY DERIVED FROM DIVERGENCE FUNCTIONS : INFORMATION GEOMETRY APPROACH (2012) (4)
Dynamics of Learning in Multilayer Perceptrons (2008) (4)
Equivalence of hidden Markov models (1991) (4)
Information geometry of turbo codes (2002) (4)
ar X iv : 1 50 5 . 04 36 8 v 1 [ q-bi o . N C ] 1 7 M ay 2 01 5 1 Measuring integrated information from the decoding perspective (2015) (4)
α-Divergence and α-Projection in Statistical Manifold (1985) (4)
A Performance Measure for Classification with Ambiguous Data (1999) (4)
Spontaneous Motion on Two-Dimensional Continuous Attractors (2015) (4)
Information geometry of neural learning and belief propagation (2002) (4)
Fast Converging Filtered Regressor Algorithms for Blind Equalization (1996) (4)
On Some Testing of Hypothesis Problems with Information Constraints (2001) (3)
Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems (1999) (3)
On-Line Learning in Neural Networks: Annealed On-line Learning in Multilayer Neural Networks (1999) (3)
The Lob-Pass Problem (2000) (3)
21aWB-2 Dynamics of Learning in Multilayer Perceptrons near the Singularity (2007) (3)
Information Geometry and the EM Algorithm (1994) (3)
Natural Gradient Learning and Its Dynamics in Singular Regions (2016) (3)
Optimal transportation plans with escort entropy regularization (2021) (3)
Standard Divergence in Manifold of Dual Affine Connections (2015) (3)
Unfaithful population decoding (2000) (3)
Information Geometry and Manifolds of Neural Networks (1994) (3)
Dual cascade networks for blind signal extraction (1997) (3)
Natural Gradient Learning Algorithms for Decorrelation (1997) (3)
Similarity Measures and Generalized Divergences (2009) (3)
Information geometry of multilayer perceptron (2004) (3)
A Theory of Nerve Nets (1974) (3)
Designing regularizers by minimizing generalization errors (1998) (3)
Natural Gradient Approach to Independent Component Analysis (2002) (3)
DYNAMICS OF EXCITATION PATTERNS IN LATERAL INHIBITORY NEURAL FIELDS. (1978) (3)
Population Coding, Bayesian Inference and Information Geometry (2005) (3)
Information geometry for turbo decoding (2005) (3)
Learning and generalization in neural networks (1995) (2)
Part 1: Tutorial series on brain-inspired computing (2005) (2)
The EM algorithm and information geometry in neural networks (1995) (2)
О некоторых задачах проверки гипотез с информационными ограничениями@@@On some testing of hypothesis problems with information constraints (2000) (2)
A theoretical study of recognition of moving objects by monocular vision (1985) (2)
Eigenvalue Analysis on Singularity in RBF networks (2007) (2)
Adaptive Blind Deconvolution and Equalization with Self-Adaptive Nonlinearities: An Information-theoretic Approach (1997) (2)
Statistical Neurodynamics — Associative Memory and Self-Organization (1989) (2)
C. R. Rao's century (2020) (2)
Blind signal separation: mathematical foundations of ICA, sparse component analysis, and other techniques (2005) (2)
Dually flat structure with escort probability and its application to alpha-Voronoi diagrams (2010) (2)
Analysis of Feasible Solutions of the ICA Problem Under the One-Bit-Matching Condition (2006) (2)
Generalization Error and Training Error at Singularities of Multilayer Perceptrons (2001) (2)
BSC: Testing of Hypotheses with Information Constraints (2000) (2)
Geometric Approach to Multilayer Perceptrons (2005) (2)
Wasserstein statistics in 1D location-scale model (2020) (2)
Maximum likelihood learning of RBMs with Gaussian visible units on the Stiefel manifold (2016) (2)
Thanks to Referees (2011) (2)
Data compression and statistical inference (1987) (2)
Introduction to Blind Signal Processing: Problems and Applications (2002) (2)
On Some Estimation Problems with Information Constraints (2002) (2)
The Pontryagin Forms of Hessian Manifolds (2015) (2)
Online Learning Dynamics of Radial Basis Function Neural Networks near the Singularity (2006) (2)
Introduction to Special Issue on Independent Components Analysis (2003) (2)
Information geometry (2021) (2)
New Consideration on Criteria of Model Selection (2003) (2)
On Density Estimation under Relative Entropy Loss Criterion (2002) (2)
Modeling Memory Transfer and Saving in Cerebellar Motor Learning (2005) (2)
Comparison of ICA/BSS algorithms for noisy data (2000) (2)
State concentration measure of quickness in Kauffman-type networks (2012) (1)
Theory of Self-Organizing Nerve Nets with Special Reference to Association and Concept Formation (1979) (1)
Information Geometry as Applied to Neural Spike Data (2014) (1)
Brain as a biocomputer. (1985) (1)
Principal/Minor Component Analysis and Related Problems (2002) (1)
Robust Techniques for BSS and ICA with Noisy Data (2002) (1)
Di erential Geometry of Estimating functions in Semiparametric Statistical Models (1993) (1)
MULTICHANNEL BLIND SEPARATION ANDDECONVOLUTION OF SOURCES WITHARBITRARY (1997) (1)
Dynamic behavior of the robust decorrelation process (2000) (1)
О некоторых задачах оценивания с информационными ограничениями@@@On Some Estimation Problems with Information Constraints (2001) (1)
Analysis of Source Sparsity and Recoverability for SCA Based Blind Source Separation (2006) (1)
On the Topological Representation of Signals in Self-Organizing Nerve Fields (1987) (1)
Chapter 8. Selected Applications (2009) (1)
Statistical Theory of Learning Curves (2007) (1)
Robust Computation in Two Dimensional Neural Field (2013) (1)
The Tracking Speed of Continuous Attractors (2007) (1)
Invariant Geometry of Manifold of Probability Distributions (2016) (1)
Achieving precise mechanical control in intrinsically noisy systems (2013) (1)
Information Geometry of Loopy BP (2003) (1)
Supereciency in Blind Source Separation (1)
Multiterminal estimation theory (1989) (1)
Information Geometry of Neuro-Manifolds (1998) (1)
The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities (2002) (1)
Geometrical Theory on Estimation of Structural Parameter in the Presence of Infinitely Many Nuisance Parameters (1983) (1)
Semiparametric Approach to Blind Deconvolution (1999) (1)
Belief propagation and turbo code: Information geometrical view (2001) (1)
Comparison of single spike train descriptive models by information geometric measure (2005) (1)
Prediction error of stochastic learning machine (1994) (1)
Formation of cortical cognitive map by self-organization (1993) (1)
On the Dual Yielding and Related Problems (1968) (1)
Mathematical Methods of Neurodynamics and Self-Organization (1988) (1)
Geometry of Learning in Multilayer Perceptrons (2004) (1)
[The Geometry of Asymptotic Inference]: Comment (1989) (1)
New Developments of Theory of Neural Networks (1994) (1)
Information Geometry and Neural Networks (1998) (0)
Neural population representation hypothesis of visual flow and its illusory after effect in the brain: psychophysics, neurophysiology and computational approaches (2012) (0)
GEOMETRY OF RANDOM DEEP NEURAL NETWORKS: INFORMATION GEOMETRY POINT OF VIEW (2021) (0)
Nonlinear State Space Models – Semi‐Blind Signal Processing (2002) (0)
Self-Whitening Adaptive Equalization andDeconvolution (1998) (0)
TLS and Its Improvements by Semiparametric Approach (2002) (0)
FOREWORD (Special Section on Nonlinear Theory and its Applications (NOLTA)) (1996) (0)
Bayes factor analysis for detection of time-dependent higher-order spike correlations (2009) (0)
\alpha -Geometry, Tsallis q-Entropy and Positive-Definite Matrices (2016) (0)
Hessian Information Geometry (chaired by Shun-Ichi Amari, Michel Nguiffo Boyom) (2015) (0)
INCF Japan Node and Platforms (2010) (0)
Parametric Statistical Models and Likelihood - O.E. Bamdorff-Nielsen. (1990) (0)
A new discriminant NMF algorithm and its application to the extraction of subtle emotional differences in speech (2012) (0)
Estimating Functions and Superefficiency for ICA and Deconvolution (2002) (0)
Preface (2019) (0)
Intelligent adaptable systems (2002) (0)
to Blind Signal Processing : Problems and (2002) (0)
Natural Gradient Learning and its Applications (2001) (0)
Neural population representation hypothesis of visual flow and its illusory after effect in the brain: psychophysics, neurophysiology and computational approaches (2012) (0)
Information Geometry of Stochastic Multilayer Perceptron (1994) (0)
Information Geometry of Belief Propagation (2004) (0)
and Method of (2018) (0)
Elements of Differential Geometry (2016) (0)
Neural Information Processing (1987) (0)
Engaging Plan for Neuroinformatics in RIKEN BSI (1999) (0)
Mathematical Theory of Neural Networks: A Personal and Historical Survey (2013) (0)
Japanese Neuroinformatics Project in Vision and RIKEN Brain Science Institute (2004) (0)
I T ] 7 S ep 2 01 7 Geometry of Information Integration (2018) (0)
Differential geometry of estimating functions (1993) (0)
Adaptive Natural Gradient Learning Based on Riemannian Metric of Score Matching (2016) (0)
Estimation and learning of network parameters in semiparametric stochastic perceptron (1994) (0)
Organized Science and Creativity (1999) (0)
Future Perspective of 'Creating Brain' Program (1998) (0)
Self-Consistent Learning of the Environment (2012) (0)
Bibliography Referenced Bibliography (1977) (0)
Appendix B: Glossary of Symbols and Abbreviations (2002) (0)
An Efficient Learning Algorithm Using Naturla Gradient and Second Order Information of Error Surface (2000) (0)
Extended SMART Algorithms for Non-negative (2006) (0)
1 Introduction – Problem Statements and Models (0)
Statistical Approach to Neural Learning and Population Coding ― From Mathematical Neuroscience (0)
Curvature of Hessian Manfiolds (2013) (0)
Mutual Information of Three-State Low Activity Diluted Neural Networks with Self-Control (1998) (0)
Piecewise-linear division of region by neural networks with maximum detectors (1994) (0)
THE INSTITUTEOFELECTRONICS, INFORMATIONAND COMMUNICATIONENGINEERSOfficers (1992 Term) (1992) (0)
Shun-ichi Amari awarded the 2019 Order of Culture (2019) (0)
Dual Affine Connections and Dually Flat Manifold (2016) (0)
Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel (2022) (0)
Blind Filtering and Separation Using a State‐Space Approach (2002) (0)
Mathematical Approach to Information and Brain (2007) (0)
Independent component analysis, sparse component analysis and non-negative matrix factorization (2005) (0)
Stochastic Perceptron and Semiparametric Statistical Inference (1993) (0)
Asymptotic Theory of Statistical Inference (2016) (0)
Curved Exponential Families and Edgeworth Expansions (1985) (0)
Information, Ancillarity and Conditional Inference (1985) (0)
An Experimental Study on Asymptotic Learning Curves (1995) (0)
Information content of neural networks with self-control and variable activity (2001) (0)
Lp-Regularized Least Squares (0 (2013) (0)
Neural Computing* (Extended Abstract) (1991) (0)
Asymptotic Theory of Tests and Interval Estimators (1985) (0)
[Brain and Artificial Intelligence]. (2019) (0)
Neural mechanisms of information processing in the brain (1987) (0)
Annealed On-Line Learning in a Nonlinear Neural Net (1997) (0)
Memory mechanisms and principles of neurocomputing (1990) (0)
Estimation in the Presence of Hidden Variables (2016) (0)
Fast-Converging Filtered Regressor Algorithms for (1996) (0)
H1.1 Mathematical theories of neural networks (1997) (0)
Higher-order correlations and a new invariant decomposition of entropy (1999) (0)
Multichannel Blind Deconvolution: Natural Gradient Approach (2002) (0)
Appendix A: Mathematical Preliminaries (2002) (0)
Iterative design of regularizers based on data by minimizing generalization errors (2000) (0)
Independent Component Analysis (ICA) and Method of Estimating Functions (5th Workshop on Stochastic Numerics) (2001) (0)
Neuroinformatics - Introduction (2003) (0)
Manifold, Divergence and Dually Flat Structure (2016) (0)
Statistical learning by natural gradient descent (2002) (0)
Microscopic instability in recurrent neural networks. (2015) (0)
On the condition for fast neural computation (2009) (0)
Learning Complex Representations from Spatial Phase Statistics of Natural Scenes (2017) (0)
On Critical Paths of ℓp-constrained Underdetermined Least Square Problem (0 (2012) (0)
Can Critical-Point Paths Under ℓp-Regularization (0 (2014) (0)
Singularities in neural networks make Bayes generalization errors smaller even if they do not contain the true (2002) (0)
[Memory--8. Mathematical model of neural pathways and memory]. (1985) (0)
Correction to: Information Geometry and Its Applications (2020) (0)
Data compression in multiterminal statistical inference —linear-threshold encoding (2011) (0)
Statistical inference under multiterminal data compression (invited paper) (2000) (0)
The Amygdaloid Kindling Phenomenon: A Tentative Model (1977) (0)
Computations Inspired from the Brain (2010) (0)
Solving a System of Algebraic Equations and Related Problems (2002) (0)
Information Geometry of Turbo Code And Gallager Code. (2001) (0)
Forty Years of Perceptrons (2001) (0)
Book review (1990) (0)
Associate Editors :N. S COTT BARKER ,G EORG BOECK ,K WOK-KEUNG M. CHENG ,J AE-SUNG RIEH ,C OSTAS D. SARRIS, AND LEI ZHU The following members of the Review Board reviewed papers during 2009. (2010) (0)
Brain Information Science (2001) (0)
Metrics Downloaded : 0 Viewed : 0 Size : 71 . 32 KB Type : application / pdf (2019) (0)
VARIANTS OF THE KULLBACK-LEIBLER DIVERGENCE AND THEIR ROLE IN MODEL SELECTION (2006) (0)
Information and the Brain (1999) (0)
Future Research in Neural Computation (1996) (0)
[Bioinformatics from the point of view of neuroscience]. (2004) (0)
Exponential Families and Mixture Families of Probability Distributions (2016) (0)
of Statistics and Its Application Computational Neuroscience : Mathematical and Statistical Perspectives (2018) (0)
Semi-Blind Signal Processing and Identification (2001) (0)
Neyman-Scott Problem: Estimating Function and Semiparametric Statistical Model (2016) (0)
Linear Systems and Time Series (2016) (0)
The Ideal Noisy Environment for Fast Neural Computation (2006) (0)
Wasserstein statistics in one-dimensional location scale models (2021) (0)
Signal Processing and Optimization (2016) (0)
ℓp-Regularized Least Squares (0 (2016) (0)
Singularities in Learning Models : Gaussian Random Field Approach (2007) (0)
Information geometry connecting Wasserstein distance and Kullback–Leibler divergence via the entropy-relaxed transportation problem (2018) (0)
Projected Gradient Algorithms (2009) (0)
Divergence, Signal Decomposition and Information Geometry (2009) (0)
Information Geometry : VIII Learning and Singularity in Neuromanifold (2005) (0)
Optimal transportation plans with escort entropy regularization (2021) (0)
Creating the Brain—CREST Program (2000) (0)
A Neural Model for the Handling of Phenomena Associated with Trains of Light Stimuli: An Updated Version to Fit Fusion Data (1977) (0)
Differential Geometry of Systems(Mathematical Theory of Control and Systems) (1984) (0)
Data Compression in Multiterminal Statistical Inference (2011) (0)
Statistical Inference in the Presence of Nuisance Parameters (1985) (0)
Meeting details (2005) (0)
On a Theory of Precise Neural Control in a Noisy System (2013) (0)

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