CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks. - Akhilan Boopathy; Tsui-Wei Weng; Pin-Yu Chen; Sijia Liu 001; Luca Daniel (AAAI, 2019)

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach. - Lily Weng; Pin-Yu Chen; Lam M. Nguyen; Mark S. Squillante; Akhilan Boopathy; Ivan V. Oseledets; Luca Daniel (ICML, 2019)

Proper Network Interpretability Helps Adversarial Robustness in Classification. - Akhilan Boopathy; Sijia Liu 001; Gaoyuan Zhang; Cynthia Liu; Pin-Yu Chen; Shiyu Chang; Luca Daniel (ICML, 2020)

Fast Training of Provably Robust Neural Networks by SingleProp. - Akhilan Boopathy; Lily Weng; Sijia Liu 001; Pin-Yu Chen; Gaoyuan Zhang; Luca Daniel (AAAI, 2021)

Fast Training of Provably Robust Neural Networks by SingleProp. - Akhilan Boopathy; Tsui-Wei Weng; Sijia Liu 001; Pin-Yu Chen; Gaoyuan Zhang; Luca Daniel (CoRR, 2021)

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

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

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

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)

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)

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)

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)