Akhilan Boopathy

About Akhilan Boopathy

Akhilan Boopathy, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Massachusetts Institute of Technology,

His recent articles reflect a diverse array of research interests and contributions to the field:

Resampling-free Particle Filters in High-dimensions

Divergence at the interpolation threshold: Identifying, interpreting & ablating the sources of a deep learning puzzle

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

Towards Exact Computation of Inductive Bias

Breaking Neural Network Scaling Laws with Modularity

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building

Rapid Learning without Catastrophic Forgetting in the Morris Water Maze

Neuro-Inspired Efficient Map Building via Fragmentation and Recall

Akhilan Boopathy Information

University

Position

___

Citations(all)

314

Citations(since 2020)

314

Cited By

89

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

Google Scholar

Top articles of Akhilan Boopathy

Resampling-free Particle Filters in High-dimensions

arXiv preprint arXiv:2404.13698

2024/4/21

Divergence at the interpolation threshold: Identifying, interpreting & ablating the sources of a deep learning puzzle

2023/11/7

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

arXiv preprint arXiv:2310.17537

2023/10/26

Towards Exact Computation of Inductive Bias

2023/10/13

Breaking Neural Network Scaling Laws with Modularity

2023/10/13

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building

2023/10/13

Rapid Learning without Catastrophic Forgetting in the Morris Water Maze

2023/10/13

Jaedong Hwang
Jaedong Hwang

H-Index: 1

Akhilan Boopathy
Akhilan Boopathy

H-Index: 2

Neuro-Inspired Efficient Map Building via Fragmentation and Recall

arXiv preprint arXiv:2307.05793

2023/7/11

Model-agnostic measure of generalization difficulty

2023/7/3

Akhilan Boopathy
Akhilan Boopathy

H-Index: 2

Jaedong Hwang
Jaedong Hwang

H-Index: 1

Framework for certifying a lower bound on a robustness level of convolutional neural networks

2023/4/11

Double descent demystified: Identifying, interpreting & ablating the sources of a deep learning puzzle

arXiv preprint arXiv:2303.14151

2023/3/24

Efficient Exploration via Fragmentation and Recall

2022/9/29

Interpretability-aware adversarial attack and defense method for deep learnings

2022/7/26

How to train your wide neural network without backprop: An input-weight alignment perspective

2022/6/28

Akhilan Boopathy
Akhilan Boopathy

H-Index: 2

Ila Fiete
Ila Fiete

H-Index: 19

Towards More Generalizable Neural Networks via Modularity

2022

Akhilan Boopathy
Akhilan Boopathy

H-Index: 2

Fast training of provably robust neural networks by singleprop

Proceedings of the AAAI Conference on Artificial Intelligence

2021/5/18

Akhilan Boopathy
Akhilan Boopathy

H-Index: 2

Sijia Liu
Sijia Liu

H-Index: 13

Proper network interpretability helps adversarial robustness in classification

2020/11/21

Akhilan Boopathy
Akhilan Boopathy

H-Index: 2

Sijia Liu
Sijia Liu

H-Index: 13

See List of Professors in Akhilan Boopathy University(Massachusetts Institute of Technology)