Mahesan Niranjan

Q: What Schools Are Affiliated With Mahesan Niranjan

Mahesan Niranjan is affiliated with the following schools: University of Sheffield, Imperial College London, University of Oxford, University of Cambridge, University of Southampton

Mahesan Niranjan's AcademicInfluence.com Rankings

Mahesan Niranjan

Computer Science

#9766

World Rank

#10246

Historical Rank

Machine Learning

#4366

World Rank

#4416

Historical Rank

Artificial Intelligence

#4718

World Rank

#4781

Historical Rank

Database

#6724

World Rank

#6961

Historical Rank

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Computer Science

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Mahesan Niranjan'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

On-line Q-learning using connectionist systems (1994) (1525)
A Function Estimation Approach to Sequential Learning with Neural Networks (1993) (475)
A theoretical investigation into the performance of the Hopfield model (1990) (402)
Sequential Monte Carlo Methods to Train Neural Network Models (2000) (221)
Neural networks and radial basis functions in classifying static speech patterns (1990) (122)
On Acoustic Emotion Recognition: Compensating for Covariate Shift (2012) (105)
Financial news predicts stock market volatility better than close price (2018) (89)
Deep Cascade Learning (2018) (81)
Realisable Classifiers: Improving Operating Performance on Variable Cost Problems (1998) (74)
Data-dependent kernels in svm classification of speech patterns (2000) (73)
FMix: Enhancing Mixed Sample Data Augmentation (2020) (72)
Trendminer: An Architecture for Real Time Analysis of Social Media Text (2012) (71)
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios (2012) (55)
Hierarchical Bayesian-Kalman models for regularisation and ARD in sequential learning (1997) (53)
Parametric subspace modeling of speech transitions (1999) (48)
Reducing the variability in cDNA microarray image processing by Bayesian inference (2004) (47)
Genomic Analysis of the Function of the Transcription Factor gata3 during Development of the Mammalian Inner Ear (2009) (46)
The past, present, and future of neural networks for signal processing (1997) (43)
Uncertainty in geometric computations (2002) (43)
Sequential Monte Carlo Methods for Neural Networks (2001) (42)
State and parameter estimation of the heat shock response system using Kalman and particle filters (2012) (41)
Sequential support vector machines (1999) (41)
Sequential Tracking in Pricing Financial Options using Model Based and Neural Network Approaches (1996) (41)
Parcel: Feature Subset Selection in Variable Cost Domains (1998) (40)
Single-cell transcriptional analysis to uncover regulatory circuits driving cell fate decisions in early mouse development (2015) (40)
Hierarchical Bayesian Models for Regularization in Sequential Learning (2000) (38)
Fully vector-quantized neural network-based code-excited nonlinear predictive speech coding (1994) (37)
Pruning with Replacement on Limited Resource Allocating Networks by F-Projections (1996) (37)
Asymptotic Mean and Variance of Gini Correlation for Bivariate Normal Samples (2010) (37)
A Dynamic Neural Network Architecture by Sequential Partitioning of the Input Space (1993) (37)
Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics (2014) (36)
A probabilistic model for the extraction of expression levels from oligonucleotide arrays. (2003) (36)
Unbalanced Decision Trees for multi-class classification (2007) (34)
Sequential Monte Carlo methods for optimisation of neural network models (1998) (34)
Comparison of Four Machine Learning Methods for Predicting PM10 Concentrations in Helsinki, Finland (2002) (33)
Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-series Prediction (1990) (33)
Design of a Low-Power On-Body ECG Classifier for Remote Cardiovascular Monitoring Systems (2013) (32)
Gaussian Markov random field based improved texture descriptor for image segmentation (2014) (31)
On the Practical Applicability of VC Dimension Bounds (1995) (30)
Enriching Texture Analysis with Semantic Data (2013) (30)
A Review of Codebook Models in Patch-Based Visual Object Recognition (2012) (29)
Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology (2017) (29)
Rotation invariant texture descriptors based on Gaussian Markov random fields for classification (2016) (27)
A comparison of multitask and single task learning with artificial neural networks for yield curve forecasting (2019) (26)
Bridging the gap between transcriptome and proteome measurements identifies post-translationally regulated genes (2013) (25)
Sequential Bayesian Decoding with a Population of Neurons (2003) (24)
Rank Selection in Nonnegative Matrix Factorization using Minimum Description Length (2017) (24)
Clinical validation of an artificial neural network trained to identify acute allograft rejection in liver transplant recipients (2001) (24)
Applying Cost-Sensitive Multiobjective Genetic Programming to Feature Extraction for Spam E-mail Filtering (2008) (23)
Understanding and Enhancing Mixed Sample Data Augmentation (2020) (21)
Design, construction and evaluation of systems to predict risk in obstetrics. (1997) (21)
Online Variational Inference for State-Space Models with Point-Process Observations (2011) (21)
Genome-Wide Posttranscriptional Dysregulation by MicroRNAs in Human Asthma as Revealed by Frac-seq (2018) (20)
Social Event Detection Via Sparse Multi-modal Feature Selection and Incremental Density Based Clustering (2013) (20)
Transfer learning across human activities using a cascade neural network architecture (2019) (19)
Markov Chain Monte Carlo Methods for State-Space Models with Point Process Observations (2012) (19)
Improved understanding of aqueous solubility modeling through topological data analysis (2018) (18)
A one-pass resource-allocating codebook for patch-based visual object recognition (2010) (18)
Partial correlation financial networks (2020) (17)
A nonlinear model for time series prediction and signal interpolation (1991) (17)
Gaussian process modelling for bicoid mRNA regulation in spatio-temporal Bicoid profile (2012) (16)
Dynamic Learning with the EM Algorithm for Neural Networks (2000) (16)
Average-Case Learning Curves for Radial Basis Function Networks (1997) (16)
Extractive summarization of voicemail using lexical and prosodic feature subset selection (2001) (16)
Automatic Face Recognition Using Stereo Images (2006) (16)
Sinhala-Tamil Machine Translation: Towards better Translation Quality (2014) (15)
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation (2011) (15)
Prediction of Gene Expression in Embryonic Structures of Drosophila melanogaster (2007) (15)
On the Trade-Off of Accuracy and Computational Complexity for Classifying Normal and Abnormal ECG in Remote CVD Monitoring Systems (2012) (15)
Generalising the nodes of the error propagation network (1989) (15)
An hmm-based cepstral-domain speech enhancement system (1994) (14)
SUBSPACE MODELS FOR SPEECH TRANSITIONS USING PRINCIPAL (1998) (14)
The EM algorithm and neural networks for nonlinear state space estimation (1998) (13)
Recursive tracking of formants in speech signals (1994) (12)
Handling phrase reorderings for machine translation (2009) (12)
Approximate low-rank factorization with structured factors (2010) (12)
Robust Portfolio Risk Minimization Using the Graphical Lasso (2017) (12)
Inferring Time-Delayed Gene Regulatory Networks Using Cross-Correlation and Sparse Regression (2013) (12)
Extending the feature set of a data-driven artificial neural network model of pricing financial options (2016) (12)
On the design of nonlinear speech predictors with recurrent nets (1994) (12)
Outlier detection at the transcriptome-proteome interface (2015) (11)
Remote Homology Detection Using a Kernel Method that Combines Sequence and Secondary-Structure Similarity Scores (2009) (11)
Estimating a State-Space Model from Point Process Observations: A Note on Convergence (2010) (11)
Regularisation in Sequential Learning Algorithms (1997) (11)
Transfer learning efficiently maps bone marrow cell types from mouse to human using single-cell RNA sequencing (2020) (11)
Temporal decomposition: a framework for enhanced speech recognition (1989) (10)
Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality (2020) (10)
Tile optimization for area in FPGA based hardware acceleration of peptide identification (2011) (10)
Support vector machines: a tutorial overview and critical appraisal (1999) (10)
Statistical Machine Translation from and into Morphologically Rich and Low Resourced Languages (2015) (10)
MIAT: A novel attribute selection approach to better predict upper gastrointestinal cancer (2015) (10)
Deterministic and Statistical Methods in Machine Learning, First International Workshop, Sheffield, UK, September 7-10, 2004, Revised Lectures (2005) (10)
On modelling the dynamics of speech patterns (1987) (10)
Classification with binary gene expressions (2009) (10)
Models of dynamic complexity for time-series prediction (neural networks) (1992) (10)
A numerical measure of the instability of Mapper-type algorithms (2019) (10)
Nonlinear predictive vector quantisation with recurrent neural nets (1993) (9)
Quantitative analysis of pulmonary emphysema using isotropic Gaussian Markov random fields (2014) (9)
Speech Modelling Using Subspace and EM Techniques (1999) (9)
Quantifying Influence in Financial Markets via Partial Correlation Network Inference (2019) (9)
Nonlinear state space learning with EM and neural networks (1998) (8)
Feature selection using expected attainable discrimination (1998) (8)
Maximum Realisable Performance: a Principled Method for Enhancing Performance by Using Multiple Clas (1998) (8)
The Role of Regulated mRNA Stability in Establishing Bicoid Morphogen Gradient in Drosophila Embryonic Development (2011) (8)
Unsupervised Texture Segmentation using Active Contours and Local Distributions of Gaussian Markov Random Field Parameters (2012) (8)
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning (2004) (8)
Reducing the algorithmic variability in transcriptome-based inference (2010) (8)
Inducing discrimination in biologically inspired models of visual scene recognition (2013) (8)
Distance phrase reordering for MOSES - User Manual and Code Guide (2010) (8)
Geometrical techniques for finding the embedding dimension of time series (1996) (7)
Comparison of Four Machine Learning Methods for Predicting PM 10 Concentrations in Helsink (2002) (7)
Construction of Minimum Spanning Trees from Financial Returns using Rank Correlation (2020) (7)
Mapping biology from mouse to man using transfer learning (2019) (7)
Nonlinear State Space Estimation With Neural Networks And The Em Algorithm (1999) (7)
A Variational Autoencoder for Probabilistic Non-Negative Matrix Factorisation (2018) (7)
CELP coding with adaptive output-error model identification (1990) (7)
Bayesian processing of microarray images (2003) (6)
Speeding up multi-class texture classification by one-pass vocabulary design and decision tree (2011) (6)
Nonlinear adaptive filtering in nonstationary environments (1991) (6)
Outlier Detection in Benchmark Classification Tasks (2006) (6)
Structure learning for natural language processing (2009) (6)
Inference from Low Precision Transcriptome Data Representation (2010) (6)
Markov chain Monte Carlo methods for speech enhancement (1998) (6)
Limits on the Discrimination Possible with Discrete Valued Data, with Application to Medical Risk Prediction Limits on the Discrimination Possible with Discrete Valued Data, with Application to Medical Risk Prediction (1996) (6)
Global optimisation of neural network models via sequential sampling-importance resampling (1998) (6)
Neural Networks for Signal Processing VIII : proceedings of the 1998 IEEE Signal Processing Society Workshop (1998) (6)
An improved speech production model for voiced speech utilising seasonal AR-AR model and Markov chain Monte Carlo simulation (1998) (6)
Texture classification with fisher kernel extracted from the continuous models of RBM (2015) (6)
Speech Processing Using Bayesian Inference (1993) (6)
Speech enhancement in a Bayesian framework (1998) (6)
Speaker Adaptation Applied to Sinhala Speech Recognition (2015) (6)
TransformerGO: predicting protein–protein interactions by modelling the attention between sets of gene ontology terms (2022) (5)
On the use of Expected Attainable Discrimination for feature selection in large scale medical risk p (1997) (5)
Markov chain Monte Carlo estimation for the seasonal autoregressive process with application to pitch modelling (1998) (5)
Vocal tract modelling with recurrent neural networks (1995) (5)
Large-scale Reordering Model for Statistical Machine Translation using Dual Multinomial Logistic Regression (2014) (5)
Compact codebook design for visual scene recognition by Sequential Input Space Carving (2013) (5)
Detection of social events in streams of social multimedia (2015) (5)
Efficient use of training data for sinhala speech recognition using active learning (2013) (5)
Parametric subspace modelling of speech transitions (1998) (5)
The application of structured learning in natural language processing (2010) (5)
An evaluation of different classification algorithms for protein sequence-based reverse vaccinology prediction (2019) (5)
The Memory Advantage of Long Short-Term Memory Networks for Bond Yield Forecasting (2019) (5)
Sequential Adaptation of Radial Basis Function Networks (1990) (5)
An efficient and speeded-up tree for multi-class classification (2012) (5)
Artificial Neural Networks in Fixed Income Markets for Yield Curve Forecasting (2018) (4)
Bayesian Reordering Model with Feature Selection (2014) (4)
Sequential Bayesian computation of logistic regression models (1999) (4)
Discriminant Subspaces of Some High Dimensional Pattern Classification Problems (2007) (4)
Non-Negative Matrix Factorization with Exogenous Inputs for Modeling Financial Data (2017) (4)
Evaluating a Machine Learning Approach to Sinhala Morphological Analysis (2013) (4)
Cross-Platform Analysis with Binarized Gene Expression Data (2009) (4)
Hybrid sequential Monte Carlo/Kalman methods to train neural networks in non-stationary environments (1999) (4)
Stability and similarity in financial networks—How do they change in times of turbulence? (2021) (4)
Towards Sinhala Tamil machine translation (2013) (4)
Scalable Reordering Models for SMT based on Multiclass SVM (2015) (3)
Parameter Estimation in Computational Biology by Approximate Bayesian Computation coupled with Sensitivity Analysis (2017) (3)
Non-linear speech transition visualization (1997) (3)
Diphone multi-trajectory subspace models (1999) (3)
Speech enhancement using a Bayesian evidence approach (2001) (3)
Sequential Hierarchical Pattern Clustering (2009) (3)
Memory-efficient large-scale linear support vector machine (2015) (3)
Application of neural networks to postoperative liver transplant monitoring (1997) (3)
Diphone subspace mixture trajectory models for HMM complementation (2002) (3)
Exploiting Long-Range Dependencies in Protein beta-Sheet Secondary Structure Prediction (2010) (3)
Why I am not a non-Bayesian? [Medical diagnostics application] (1999) (3)
Neuro-computing versus linear statistical techniques applied to liver transplant monitoring: a comparative study (2000) (3)
CI-SpliceAI—Improving machine learning predictions of disease causing splicing variants using curated alternative splice sites (2022) (3)
Enhancing Automatic Construction of Gene Subnetworks by Integrating Multiple Sources of Information (2008) (3)
A Method of Integrating Spatial Proteomics and Protein-Protein Interaction Network Data (2017) (3)
Speech Feature Extraction Using Neural Networks (1990) (3)
Room Acoustic Properties Estimation from a Single 360° Photo (2022) (2)
Long short-term memory networks and laglasso for bond yield forecasting: Peeping inside the black box (2020) (2)
Resource-Allocating Codebook for patch-based face recognition (2009) (2)
Minimum description length as an objective function for non-negative matrix factorization (2019) (2)
Machine learning for intrusion detection: Modeling the distribution shift (2010) (2)
Comparing solution methodologies for speech enhancement within a Bayesian framework (1998) (2)
Foveated convolutions: improving spatial transformer networks by modelling the retina (2019) (2)
Generalisation and regularisation by Gaussian filter convolution of radial basis function networks (1997) (2)
Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios (2012) (2)
Self-organization with a large medical database: Using GTM for prediction and clustering (1998) (2)
Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-’omics analysis (2019) (2)
D3.2.1 Clustering models for discovery of regional and demographic variation (2013) (2)
A Biologically Inspired Visual Working Memory for Deep Networks (2019) (2)
Saliency Map on Cnns for Protein Secondary Structure Prediction (2019) (2)
Establishment of a Diagnostic Decision Support System in Genetic Dysmorphology (2012) (2)
Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009) (2)
Genome-wide post-transcriptional dysregulation by microRNAs in human asthma as revealed by Frac-seq (2017) (2)
Depth Estimation from a Single Omnidirectional Image using Domain Adaptation (2021) (2)
BUILDING ENERGY DATA ANALYSIS AND PREDICTION WITH RECURRENT NEURAL NETWORK (1993) (2)
Information Bottleneck Theory Based Exploration of Cascade Learning (2021) (2)
The application of Bayesian inference to linear prediction of speech (1994) (2)
On Comparing the Influences of Exogenous Information on Bitcoin Prices and Stock Index Values (2019) (1)
OPBI: An open pipeline for biomarker identification (2017) (1)
Diphone subspace models for phone-based HMM complementation (1999) (1)
Dynamic Indian Sign Language Character Recognition: Using HOG Descriptor and a Customized Neural Network (2014) (1)
Sequential Inference and Learning (1998) (1)
PATTERN RECOGNITION IN BIOINFORMATICS, PROCEEDINGS (2009) (1)
Ranking the Eeect of Diierent Features on the Classiication of Discrete Valued Data (2007) (1)
Computational Models of Object Recognition - Goal, Role and Success (2014) (1)
Matching Models to Data in Modelling Morphogen Diffusion (2009) (1)
D3.1.1 Regression models of trends in streaming data (2012) (1)
Establishment of Diagnostic Decision Support System (DDSS) in Clinical Diagnosis of Genetic Diseases: The FaceGP DDSS Methodology and Its Applications (2012) (1)
The use of maximum a posteriori parameters in linear prediction of speech (1995) (1)
Classification and Regression Analysis of Lung Tumors from Multi-level Gene Expression Data (2019) (1)
Modelling uncertainty in transcriptome measurements enhances network component analysis of yeast metabolic cycle (2009) (1)
Defining the Gold Standard Definitions for the Morphology of Sinhala Words (2015) (1)
Subspaces of text discrimination with application to biological literature (2003) (1)
An Inhomogeneous Bayesian Texture Model for Spatially Varying Parameter Estimation (2014) (1)
Generative and Discriminative Reordering Models for Statistical Machine Translation (2016) (1)
A structured hardware software architecture for peptide based diagnosis — Sub-string matching problem with limited tolerance (2014) (1)
Representation-dimensionality Trade-off in Biological Sequence-based Inference (2019) (1)
The AI for Scientific Discovery Network+ (2021) (1)
Matched filter design for diphone subspace models (2000) (1)
A Review of Reinforcement Learning in Chemistry (2022) (1)
USING UPPER BOUNDS ON ATTAINABLEDISCRIMINATION TO SELECT DISCRETEVALUED (1996) (0)
Handling phrase reordering for machine translation (2009) (0)
D5.4: Sequential Algorithms (2014) (0)
Variational Autoencoder for Non-Negative Matrix Factorization with Exogenous Inputs Applied to Financial Data Modelling (2019) (0)
Title Asymptotic mean and variance of gini correlation for bivariatenormal samples (2010) (0)
LSTM-LagLasso for bond yield forecasting: Peeping into the long short-term memory networks' black box (2020) (0)
Subspace techniques in speech enhancement (1999) (0)
Automated gastrointestinal abnormalities detection from endoscopic images (2021) (0)
Speech signal modelling with sparse autoregression (2009) (0)
Multi-class Classification on "VINE" Structure (2011) (0)
Genetic Algorithm with Rank Selection optimises robust parameter estimation for systems biology models (2022) (0)
A structured hardware software architecture for peptide based diagnosis of Baylisascaris Procyonis infection (2014) (0)
Examples in Medical Applications (1997) (0)
Speech enhancement based on artificial neural networks forhearing-impaired listeners using auditory inspired features (2016) (0)
Book Reviews (1953) (0)
Robustness under parameter and problem domain alterations of Bayesian optimization methods for chemical reactions (2022) (0)
Speech Modelling: Models, Parameter Estimation and Its Application to Speech Enhancement (1999) (0)
Detection of social events in streams of social multimedia (2015) (0)
Predicting Relative Protein Abundance via Sequence-Based Information (2021) (0)
Supplementary material from "Robust subspace methods for outlier detection in genomic data circumvents the curse of dimensionality" (2020) (0)
Depth Estimation for a Single Omnidirectional Image with Reversed-Gradient Warming-up Thresholds Discriminator (2023) (0)
the Pattern Recognition in Bioinformatics conference, Nijmegen, the Netherlands (2010) (0)
Estimation of Gaussian mixture models via tensor moments with application to online learning (2020) (0)
Convex Multi-View Clustering Via Robust Low Rank Approximation With Application to Multi-Omic Data (2021) (0)
On Sequential Bayesian Logistic Regression (1999) (0)
A Review of Codebook Models in Patch-Based Visual Object Recognition (2011) (0)
Mining Protein Database using Machine Learning Techniques (2008) (0)
Keynote speeches: Video Forgery and motion editing (2013) (0)
Mining Protein Databases using Machine Learning Techniques (2008) (0)
Deep Cascade Learning for Optimal Medical Image Feature Representation (2022) (0)
D3.1.2 Regression models of trends Tools for Mining Non-stationary Data: functional prototype (2013) (0)
Transfer learning efficiently maps bone marrow cell types from mouse to human using single-cell RNA sequencing (2020) (0)
Robust 3D rotation invariant local binary pattern for volumetric texture classification (2022) (0)
Computational models of machine vision goal, role and success (2014) (0)
A Novel Approach to Improve the Diagnostic Success of Computers in Dysmorphology: The DSESPC methodology and its Applications (2013) (0)
On the statistical physics of radial basis function networks (1995) (0)
Machine learning applied to HR-pQCT images improves fracture discrimination provided by DXA and clinical risk factors. (2022) (0)
Uncovering extensive post-translation regulation during human cell cycle progression by integrative multi-’omics analysis (2019) (0)
MARKOV CHAINMONTE CARLO ESTIMATION FOR THE SEASONAL AUTOREGRESSIVE PROCESS WITH APPLICATION TO PITCHMODELLING (1998) (0)

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What Schools Are Affiliated With Mahesan Niranjan?

Mahesan Niranjan is affiliated with the following schools:

Mahesan Niranjan's Academic­Influence.com Rankings

Why Is Mahesan Niranjan Influential?

Mahesan Niranjan's Published Works

Published Works

What Schools Are Affiliated With Mahesan Niranjan?

Mahesan Niranjan's AcademicInfluence.com Rankings