Accurate Path Integration in Continuous Attractor Network Models of Grid Cells. - Yoram Burak; Ila R. Fiete (PLoS Comput. Biol., 2009)

Dynamic shift-map coding with side information at the decoder. - Yongseok Yoo; Onur Ozan Koyluoglu; Sriram Vishwanath; Ila Fiete (Allerton Conference, 2012)

Multi-periodic neural coding for adaptive information transfer. - Yongseok Yoo; Onur Ozan Koyluoglu; Sriram Vishwanath; Ila Fiete (Theor. Comput. Sci., 2016)

Training recurrent networks to generate hypotheses about how the brain solves hard navigation problems. - Ingmar Kanitscheider; Ila Fiete (NIPS, 2017)

Associative content-addressable networks with exponentially many robust stable states. - Rishidev Chaudhuri; Ila Fiete (CoRR, 2017)

Kernel RNN Learning (KeRNL). - Christopher Roth; Ingmar Kanitscheider; Ila Fiete (ICLR (Poster), 2019)

Bipartite expander Hopfield networks as self-decoding high-capacity error correcting codes. - Rishidev Chaudhuri; Ila Fiete (NeurIPS, 2019)

Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice. - Rylan Schaeffer; Mikail Khona; Leenoy Meshulam; International Brain Laboratory; Ila Fiete (NeurIPS, 2020)

Efficient and flexible representation of higher-dimensional cognitive variables with grid cells. - Mirko Klukas; Marcus Lewis; Ila Fiete (PLoS Comput. Biol., 2020)

Efficient online inference for nonparametric mixture models. - Rylan Schaeffer; Blake Bordelon; Mikail Khona; Weiwei Pan; Ila Rani Fiete (UAI, 2021)

Gradient-trained Weights in Wide Neural Networks Align Layerwise to Error-scaled Input Correlations. - Akhilan Boopathy; Ila Fiete (CoRR, 2021)

Efficient exploration of spatial environments through Map Induction using adaptable compositional map representations. - Sugandha Sharma; Aidan Curtis; Marta Kryven; Josh Tenenbaum 001; Ila Fiete (CogSci, 2022)

Streaming Inference for Infinite Non-Stationary Clustering. - Rylan Schaeffer; Gabrielle Kaili-May Liu; Yilun Du; Scott Linderman; Ila Rani Fiete (CoLLAs, 2022)

Map Induction: Compositional spatial submap learning for efficient exploration in novel environments. - Sugandha Sharma; Aidan Curtis; Marta Kryven; Joshua B. Tenenbaum; Ila R. Fiete (ICLR, 2022)

How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective. - Akhilan Boopathy; Ila Fiete (ICML, 2022)

Streaming Inference for Infinite Feature Models. - Rylan Schaeffer; Yilun Du; Gabrielle K. Liu; Ila Fiete (ICML, 2022)

Content Addressable Memory Without Catastrophic Forgetting by Heteroassociation with a Fixed Scaffold. - Sugandha Sharma; Sarthak Chandra; Ila R. Fiete (ICML, 2022)

See and Copy: Generation of complex compositional movements from modular and geometric RNN representations. - Sunny Duan; Mikail Khona; Adrian Bertagnoli; Sarthak Chandra; Ila Fiete (NeurReps, 2022)

No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit. - Rylan Schaeffer; Mikail Khona; Ila Fiete (NeurIPS, 2022)

Model-agnostic Measure of Generalization Difficulty. - Akhilan Boopathy; Kevin Liu; Jaedong Hwang; Shu Ge; Asaad Mohammedsaleh; Ila Fiete (ICML, 2023)

Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis. - Mitchell Ostrow; Adam Eisen; Leo Kozachkov; Ila Fiete (NeurIPS, 2023)

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. - Rylan Schaeffer; Mikail Khona; Tzuhsuan Ma; Cristóbal Eyzaguirre; Sanmi Koyejo; Ila Fiete (NeurIPS, 2023)

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. - Rylan Schaeffer; Mikail Khona; Zachary Robertson; Akhilan Boopathy; Kateryna Pistunova; Jason W. Rocks; Ila Rani Fiete; Oluwasanmi Koyejo (CoRR, 2023)

Optimizing protein fitness using Gibbs sampling with Graph-based Smoothing. - Andrew Kirjner; Jason Yim; Raman Samusevich; Tommi S. Jaakkola; Regina Barzilay; Ila Fiete (CoRR, 2023)

Neuro-Inspired Efficient Map Building via Fragmentation and Recall. - Jaedong Hwang; Zhang-Wei Hong; Eric Chen; Akhilan Boopathy; Pulkit Agrawal 001; Ila Fiete (CoRR, 2023)

Growing Brains: Co-emergence of Anatomical and Functional Modularity in Recurrent Neural Networks. - Ziming Liu; Mikail Khona; Ila R. Fiete; Max Tegmark (CoRR, 2023)

Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity. - Jaedong Hwang; Zhang-Wei Hong; Eric Chen; Akhilan Boopathy; Pulkit Agrawal 001; Ila Fiete (CoRR, 2023)

Winning the Lottery With Neural Connectivity Constraints: Faster Learning Across Cognitive Tasks With Spatially Constrained Sparse RNNs. - Mikail Khona; Sarthak Chandra; Joy J. Ma; Ila R. Fiete (Neural Comput., 2023)

Improving protein optimization with smoothed fitness landscapes. - Andrew Kirjner; Jason Yim; Raman Samusevich; Shahar Bracha; Tommi S. Jaakkola; Regina Barzilay; Ila R. Fiete (ICLR, 2024)

Rapid Learning without Catastrophic Forgetting in the Morris Water Maze. - Raymond Wang; Jaedong Hwang; Akhilan Boopathy; Ila R. Fiete (ICML, 2024)

Resampling-free Particle Filters in High-dimensions. - Akhilan Boopathy; Aneesh Muppidi; Peggy Yang; Abhiram Iyer; William Yue; Ila Fiete (ICRA, 2024)

Towards Exact Computation of Inductive Bias. - Akhilan Boopathy; William Yue; Jaedong Hwang; Abhiram Iyer; Ila Fiete (IJCAI, 2024)

Flexible Context-Driven Sensory Processing in Dynamical Vision Models. - Lakshmi Narasimhan Govindarajan; Abhiram Iyer; Valmiki Kothare; Ila Fiete (NeurIPS, 2024)

Flexible mapping of abstract domains by grid cells via self-supervised extraction and projection of generalized velocity signals. - Abhiram Iyer; Sarthak Chandra; Sugandha Sharma; Ila Fiete (NeurIPS, 2024)

How Diffusion Models Learn to Factorize and Compose. - Qiyao Liang; Ziming Liu; Mitchell Ostrow; Ila Fiete (NeurIPS, 2024)

Do Diffusion Models Learn Semantically Meaningful and Efficient Representations? - Qiyao Liang; Ziming Liu; Ila Fiete (CoRR, 2024)

Bridging Associative Memory and Probabilistic Modeling. - Rylan Schaeffer; Nika Zahedi; Mikail Khona; Dhruv Pai; Sang T. Truong; Yilun Du; Mitchell Ostrow; Sarthak Chandra; Andres Carranza; Ila Rani Fiete; Andrey Gromov; Sanmi Koyejo (CoRR, 2024)

Delay Embedding Theory of Neural Sequence Models. - Mitchell Ostrow; Adam Eisen; Ila Fiete (CoRR, 2024)

Uncovering Latent Memories: Assessing Data Leakage and Memorization Patterns in Large Language Models. - Sunny Duan; Mikail Khona; Abhiram Iyer; Rylan Schaeffer; Ila R. Fiete (CoRR, 2024)

Unified Neural Network Scaling Laws and Scale-time Equivalence. - Akhilan Boopathy; Ila Fiete (CoRR, 2024)

ImageNet-RIB Benchmark: Large Pre-Training Datasets Don't Guarantee Robustness after Fine-Tuning. - Jaedong Hwang; Brian Cheung; Zhang-Wei Hong; Akhilan Boopathy; Pulkit Agrawal 001; Ila Fiete (CoRR, 2024)

Permutation Invariant Learning with High-Dimensional Particle Filters. - Akhilan Boopathy; Aneesh Muppidi; Peggy Yang; Abhiram Iyer; William Yue; Ila Fiete (CoRR, 2024)

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building. - Jaedong Hwang; Zhang-Wei Hong; Eric Chen; Akhilan Boopathy; Pulkit Agrawal 001; Ila R. Fiete (Trans. Mach. Learn. Res., 2024)

Breaking Neural Network Scaling Laws with Modularity. - Akhilan Boopathy; Sunshine Jiang; William Yue; Jaedong Hwang; Abhiram Iyer; Ila R. Fiete (ICLR, 2025)

Uncovering Latent Memories in Large Language Models. - Sunny Duan; Mikail Khona; Abhiram Iyer; Rylan Schaeffer; Ila R. Fiete (ICLR, 2025)

Key-value memory in the brain. - Samuel J. Gershman; Ila Fiete; Kazuki Irie (CoRR, 2025)

Paper Quality Assessment based on Individual Wisdom Metrics from Open Peer Review. - Andrii Zahorodnii; Jasper J. F. van den Bosch; Ian Charest; Christopher Summerfield; Ila R. Fiete (CoRR, 2025)

Compositional Generalization Requires More Than Disentangled Representations. - Qiyao Liang; Daoyuan Qian; Liu Ziyin 001; Ila Fiete (CoRR, 2025)

Characterizing control between interacting subsystems with deep Jacobian estimation. - Adam Eisen; Mitchell Ostrow; Sarthak Chandra; Leo Kozachkov; Earl K. Miller; Ila R. Fiete (CoRR, 2025)

Learn Globally, Speak Locally: Bridging the Gaps in Multilingual Reasoning. - Jaedong Hwang; Kumar Tanmay; Seok-Jin Lee; Ayush Agrawal; Hamid Palangi; Kumar Ayush; Ila Fiete; Paul Pu Liang (CoRR, 2025)