Ila Fiete

Q: What Schools Are Affiliated With Ila Fiete

Ila Fiete is affiliated with the following schools: University of California, Berkeley, University of Texas at Austin, California Institute of Technology, Massachusetts Institute of Technology

Ila Fiete's AcademicInfluence.com Rankings

Ila Fiete

Physics

#7349

World Rank

#9372

Historical Rank

physics Degrees

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Physics

Ila Fiete's Degrees

PhD Physics University of California, Berkeley
Bachelors Physics California Institute of Technology

Why Is Ila Fiete Influential?

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According to Wikipedia, Ila Fiete is an Indian–American physicist and computational neuroscientist as well as a Professor in the Department of Brain and Cognitive Sciences within the McGovern Institute for Brain Research at the Massachusetts Institute of Technology. Fiete builds theoretical models and analyses neural data and to uncover how neural circuits perform computations and how the brain represents and manipulates information involved in memory and reasoning.

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Ila Fiete'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

Spike-Time-Dependent Plasticity and Heterosynaptic Competition Organize Networks to Produce Long Scale-Free Sequences of Neural Activity (2010) (250)
What Grid Cells Convey about Rat Location (2008) (247)
Specific evidence of low-dimensional continuous attractor dynamics in grid cells (2013) (227)
Accurate Path Integration in Continuous Attractor Network Models of Grid Cells (2008) (204)
Grid cells generate an analog error-correcting code for singularly precise neural computation (2011) (188)
Testing Odor Response Stereotypy in the Drosophila Mushroom Body (2008) (162)
Model of birdsong learning based on gradient estimation by dynamic perturbation of neural conductances. (2007) (162)
The intrinsic attractor manifold and population dynamics of a canonical cognitive circuit across waking and sleep (2019) (162)
Computational principles of memory (2016) (160)
Gradient learning in spiking neural networks by dynamic perturbation of conductances. (2006) (113)
Temporal sparseness of the premotor drive is important for rapid learning in a neural network model of birdsong. (2004) (97)
Fundamental limits on persistent activity in networks of noisy neurons (2012) (92)
The Mind of a Mouse (2020) (86)
Grid cells: The position code, neural network models of activity, and the problem of learning (2008) (82)
A Model of Grid Cell Development through Spatial Exploration and Spike Time-Dependent Plasticity (2014) (79)
Grid cell co-activity patterns during sleep reflect spatial overlap of grid fields during active behaviors (2017) (63)
A Map-like Micro-Organization of Grid Cells in the Medial Entorhinal Cortex (2018) (62)
Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems (2016) (49)
An International Laboratory for Systems and Computational Neuroscience (2017) (49)
Do We Understand the Emergent Dynamics of Grid Cell Activity? (2006) (49)
Grid Cell Responses in 1D Environments Assessed as Slices through a 2D Lattice (2016) (48)
Systematic errors in connectivity inferred from activity in strongly recurrent networks (2020) (41)
Bias in Human Path Integration Is Predicted by Properties of Grid Cells (2015) (36)
Cortical ensembles orchestrate social competition through hypothalamic outputs (2022) (25)
Attractor and integrator networks in the brain (2021) (25)
Efficient and flexible representation of higher-dimensional cognitive variables with grid cells (2020) (24)
Reverse-engineering Recurrent Neural Network solutions to a hierarchical inference task for mice (2020) (23)
Sources of path integration error in young and aging humans (2018) (23)
Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity (2017) (19)
Neural network models of birdsong production , learning , and coding (2007) (17)
Kernel RNN Learning (KeRNL) (2018) (17)
Neurotensin orchestrates valence assignment in the amygdala (2022) (13)
A Model of Grid Cell Development through Spatial Exploration and Spike Time-Dependent Plasticity (2014) (13)
Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes (2019) (12)
Emergence of dynamically reconfigurable hippocampal responses by learning to perform probabilistic spatial reasoning (2017) (11)
No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit (2022) (10)
A binary Hopfield network with $1/\log(n)$ information rate and applications to grid cell decoding (2014) (10)
Learning and coding in biological neural networks (2003) (9)
Triangular lattice neurons may implement an advanced numeral system to precisely encode rat position over large ranges (2006) (9)
Making our way through the world: Towards a functional understanding of the brain's spatial circuits (2017) (8)
The population dynamics of a canonical cognitive circuit (2019) (8)
How does the brain solve the computational problems of spatial navigation (2014) (8)
Systematic errors in connectivity inferred from activity in strongly coupled recurrent circuits (2019) (7)
Place-cell capacity and volatility with grid-like inputs (2021) (6)
Content addressable memory without catastrophic forgetting by heteroassociation with a fixed scaffold (2022) (6)
Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells (2018) (6)
Cortical microcircuit determination through global perturbation and sparse sampling in grid cells (2015) (6)
Multi-periodic neural coding for adaptive information transfer (2016) (5)
A structured scaffold underlies activity in the hippocampus (2021) (5)
Flexible representation of higher-dimensional cognitive variables with grid cells (2019) (4)
Efficient online inference for nonparametric mixture models (2021) (4)
Associative content-addressable networks with exponentially many robust stable states (2017) (4)
Robust parallel decision-making in neural circuits with nonlinear inhibition (2019) (4)
Losing Phase (2010) (4)
Fragmented Spatial Maps from Surprisal: State Abstraction and Efficient Planning (2022) (3)
Efficient Inference in Structured Spaces (2020) (3)
From smooth cortical gradients to discrete modules : spontaneous 1 and topologically robust emergence of modularity in grid cells 2 (2022) (3)
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective (2021) (3)
Dynamic shift-map coding with side information at the decoder (2012) (2)
Gradient-trained Weights in Wide Neural Networks Align Layerwise to Error-scaled Input Correlations (2021) (2)
Spontaneous emergence of topologically robust grid cell modules: A multiscale instability theory (2021) (2)
A cortical-hypothalamic circuit decodes social rank and promotes dominance behavior (2020) (2)
Superlinear Precision and Memory in Simple Population Codes (2020) (2)
Spatial reasoning via recurrent neural dynamics in mouse retrosplenial cortex (2022) (1)
Fragmented Spatial Maps: State Abstraction and Efficient Planning from Surprisal (2021) (1)
Birdsong Learning (2011) (1)
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments (2021) (1)
A Continuous Attractor Model for Grid Cell Activity (2007) (1)
Where can a place cell put its fields? Let us count the ways (2019) (1)
How fast is neural winner-take-all when deciding between many options? (2017) (1)
Primate neocortex performs balanced sensory amplification (2022) (1)
From smooth cortical gradients to discrete modules: A biologically plausible mechanism for the self-organization of modularity in grid cells (2022) (0)
Super-linear Precision in Simple Neural Population Codes (2015) (0)
Vector production via mental navigation in the entorhinal cortex (2022) (0)
Sources of path integration error in young and aging humans (2020) (0)
Author response: Place-cell capacity and volatility with grid-like inputs (0)
Streaming Inference for Infinite Feature Models (2022) (0)
Grid cell co-activity patterns during sleep reflect spatial overlap of grid fields during active behaviors (2019) (0)
See and Copy: Generation of complex compositional movements from modular and geometric RNN representations (2022) (0)
Optimizing population coding with unimodal tuning curves and short-term memory in continuous attractor networks (2018) (0)
Author response: Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells (2018) (0)
Observed pre-motor firing patterns constrain a network model for vocal learning (2007) (0)
Winning the lottery with neurobiology: faster learning on many cognitive tasks with fixed sparse RNNs (2022) (0)
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle (2023) (0)
Systematic errors in connectivity inferred from activity in strongly recurrent networks (2020) (0)
Noisy dynamical systems evolve error correcting codes and modularity (2023) (0)
Decision letter: During hippocampal inactivation, grid cells maintain synchrony, even when the grid pattern is lost (2019) (0)
Model-agnostic Measure of Generalization Difficulty (2023) (0)
Editorial overview: Theoretical and computational approaches to decipher brain function from molecules to behavior (2021) (0)
Streaming Inference for Infinite Non-Stationary Clustering (2022) (0)
Author response: Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity (2017) (0)

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What Schools Are Affiliated With Ila Fiete?

Ila Fiete is affiliated with the following schools:

Ila Fiete's Academic­Influence.com Rankings