Akhilan Boopathy

According to our database, Akhilan Boopathy authored at least 17 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building.

Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila R. Fiete

Trans. Mach. Learn. Res., 2024

Unified Neural Network Scaling Laws and Scale-time Equivalence.

Akhilan Boopathy, Ila Fiete

CoRR, 2024

Breaking Neural Network Scaling Laws with Modularity.

Akhilan Boopathy, Sunshine Jiang, William Yue, Jaedong Hwang, Abhiram Iyer, Ila Fiete

CoRR, 2024

Towards Exact Computation of Inductive Bias.

Akhilan Boopathy, William Yue, Jaedong Hwang, Abhiram Iyer, Ila Fiete

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Resampling-free Particle Filters in High-dimensions.

Akhilan Boopathy, Aneesh Muppidi, Peggy Yang, Abhiram Iyer, William Yue, Ila Fiete

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Rapid Learning without Catastrophic Forgetting in the Morris Water Maze.

Raymond Wang, Jaedong Hwang, Akhilan Boopathy, Ila R. Fiete

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

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

Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete

CoRR, 2023

Neuro-Inspired Efficient Map Building via Fragmentation and Recall.

Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete

CoRR, 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

Model-agnostic Measure of Generalization Difficulty.

Akhilan Boopathy, Kevin Liu, Jaedong Hwang, Shu Ge, Asaad Mohammedsaleh, Ila Fiete

Proceedings of the International Conference on Machine Learning, 2023

2022

How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective.

Akhilan Boopathy, Ila Fiete

Proceedings of the International Conference on Machine Learning, 2022

2021

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

Akhilan Boopathy, Ila Fiete

CoRR, 2021

Fast Training of Provably Robust Neural Networks by SingleProp.

Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel

CoRR, 2021

Fast Training of Provably Robust Neural Networks by SingleProp.

Akhilan Boopathy, Lily Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Proper Network Interpretability Helps Adversarial Robustness in Classification.

Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu, Pin-Yu Chen, Shiyu Chang, Luca Daniel

Proceedings of the 37th International Conference on Machine Learning, 2020

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

Proceedings of the 36th International Conference on Machine Learning, 2019

CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks.

Akhilan Boopathy, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019