Ila Fiete

Orcid: 0000-0003-4738-2539

Affiliations:
  • Massachusetts Institute of Technology, Cambridge, MA, USA
  • University of Texas at Austin, TX, USA (2008-2018)
  • California Institute of Technology, Pasadena, CA, USA (2006-2008)
  • Harvard University, Cambridge, MA, USA (PhD 2004)


According to our database1, Ila Fiete authored at least 29 papers between 2009 and 2024.

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Bibliography

2024
Bridging Associative Memory and Probabilistic Modeling.
CoRR, 2024

Do Diffusion Models Learn Semantically Meaningful and Efficient Representations?
CoRR, 2024

2023
Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNs.
Neural Comput., November, 2023

Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity.
CoRR, 2023

Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks.
CoRR, 2023

Neuro-Inspired Efficient Map Building via Fragmentation and Recall.
CoRR, 2023

Optimizing protein fitness using Gibbs sampling with Graph-based Smoothing.
CoRR, 2023

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle.
CoRR, 2023

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model-agnostic Measure of Generalization Difficulty.
Proceedings of the International Conference on Machine Learning, 2023

2022
No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

See and Copy: Generation of complex compositional movements from modular and geometric RNN representations.
Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

Content Addressable Memory Without Catastrophic Forgetting by Heteroassociation with a Fixed Scaffold.
Proceedings of the International Conference on Machine Learning, 2022

Streaming Inference for Infinite Feature Models.
Proceedings of the International Conference on Machine Learning, 2022

How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective.
Proceedings of the International Conference on Machine Learning, 2022

Map Induction: Compositional spatial submap learning for efficient exploration in novel environments.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Streaming Inference for Infinite Non-Stationary Clustering.
Proceedings of the Conference on Lifelong Learning Agents, 2022

2021
Gradient-trained Weights in Wide Neural Networks Align Layerwise to Error-scaled Input Correlations.
CoRR, 2021

Efficient online inference for nonparametric mixture models.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020
Efficient and flexible representation of higher-dimensional cognitive variables with grid cells.
PLoS Comput. Biol., 2020

Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Kernel RNN Learning (KeRNL).
Proceedings of the 7th International Conference on Learning Representations, 2019

2017
Associative content-addressable networks with exponentially many robust stable states.
CoRR, 2017

Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Multi-periodic neural coding for adaptive information transfer.
Theor. Comput. Sci., 2016

2012
Dynamic shift-map coding with side information at the decoder.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2009
Accurate Path Integration in Continuous Attractor Network Models of Grid Cells.
PLoS Comput. Biol., 2009


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