Rahul Ramesh
Rahul Ramesh
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Model Zoo: A Growing "Brain" That Learns Continually
R Ramesh, P Chaudhari
International Conference on Learning Representations (ICLR 22), 2022
Successor Options: An Option Discovery Framework for Reinforcement Learning
R Ramesh, M Tomar, B Ravindran
International Joint Conference on Artificial Intelligence (IJCAI 19), 2019
Learning to factor policies and action-value functions: Factored action space representations for deep reinforcement learning
S Sharma, A Suresh, R Ramesh, B Ravindran
arXiv preprint arXiv:1705.07269, 2017
FigureNet: A Deep Learning model for Question-Answering on Scientific Plots
R Reddy, R Ramesh, A Deshpande, MM Khapra
International Joint Conference on Neural Networks (IJCNN 19), 2019
The Value of Out-of-Distribution Data
A De Silva, R Ramesh, CE Priebe, P Chaudhari, JT Vogelstein
International Conference on Machine Learning (ICML 23), 2022
Prospective Learning: Principled Extrapolation to the Future
A De Silva, R Ramesh, L Ungar, MH Shuler, NJ Cowan, M Platt, C Li, ...
Conference on Lifelong Learning Agents, 347-357, 2023
A picture of the space of typical learnable tasks
R Ramesh, J Mao, I Griniasty, R Yang, HK Teoh, M Transtrum, JP Sethna, ...
International Conference on Machine Learning (ICML 23), 2022
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning
R Ramesh*, A Manoharan*, B Ravindran
The European Conference on Machine Learning and Principles and Practice of …, 2020
The training process of many deep networks explores the same low-dimensional manifold
J Mao, I Griniasty, HK Teoh, R Ramesh, R Yang, MK Transtrum, ...
Proceedings of the National Academy of Sciences 121 (12), e2310002121, 2024
How Capable Can a Transformer Become? A Study on Synthetic, Interpretable Tasks
R Ramesh, M Khona, RP Dick, H Tanaka, ES Lubana
arXiv preprint arXiv:2311.12997, 2023
Deep Reference Priors: What is the best way to pretrain a model?
Y Gao*, R Ramesh*, P Chaudhari
International Conference on Machine Learning (ICML 22), 2022
Stepwise Inference in Transformers: Exploring a Synthetic Graph Navigation Task
M Khona, M Okawa, R Ramesh, K Nishi, RP Dick, ES Lubana, H Tanaka
R0-FoMo: Robustness of Few-shot and Zero-shot Learning in Large Foundation …, 2023
Methods, systems, and computer readable media for machine learning of multiple tasks
PA Chaudhari, R Ramesh
US Patent App. 18/112,763, 2023
AUPCR Maximizing Matchings: Towards a Pragmatic Notion of Optimality for One-Sided Preference Matchings
G Raguvir J*, R Ramesh*, S Sridhar*, V Manoharan*
Multidisciplinary Workshop on Advances in Preference Handling (AAAI 2018), 2017
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