Ramesh, Rahul

18 publications

ICCV 2025 From Linearity to Non-Linearity: How Masked Autoencoders Capture Spatial Correlations Anthony Bisulco, Rahul Ramesh, Randall Balestriero, Pratik Chaudhari

ICML 2025 Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing Kento Nishi, Rahul Ramesh, Maya Okawa, Mikail Khona, Hidenori Tanaka, Ekdeep Singh Lubana

ICML 2024 Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona, Robert P. Dick, Hidenori Tanaka

NeurIPS 2024 Prospective Learning: Learning for a Dynamic Future Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T. Vogelstein, Pratik Chaudhari

NeurIPSW 2024 Prospective Learning: Learning for a Dynamic Future Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T Vogelstein, Pratik Chaudhari

ICML 2024 Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model Mikail Khona, Maya Okawa, Jan Hula, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka

ICML 2023 A Picture of the Space of Typical Learnable Tasks Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark Transtrum, James Sethna, Pratik Chaudhari

NeurIPSW 2023 How Capable Can a Transformer Become? a Study on Synthetic, Interpretable Tasks Rahul Ramesh, Mikail Khona, Robert P. Dick, Hidenori Tanaka, Ekdeep Singh Lubana

NeurIPSW 2023 How Capable Can a Transformer Become? a Study on Synthetic, Interpretable Tasks Rahul Ramesh, Mikail Khona, Robert P. Dick, Hidenori Tanaka, Ekdeep Singh Lubana

CoLLAs 2023 Prospective Learning: Principled Extrapolation to the Future Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu Timothy Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein

NeurIPSW 2023 Stepwise Inference in Transformers: Exploring a Synthetic Graph Navigation Task Mikail Khona, Maya Okawa, Rahul Ramesh, Kento Nishi, Robert P. Dick, Ekdeep Singh Lubana, Hidenori Tanaka

ICML 2023 The Value of Out-of-Distribution Data Ashwin De Silva, Rahul Ramesh, Carey Priebe, Pratik Chaudhari, Joshua T Vogelstein

ICML 2022 Deep Reference Priors: What Is the Best Way to Pretrain a Model? Yansong Gao, Rahul Ramesh, Pratik Chaudhari

ICLR 2022 Model Zoo: A Growing Brain That Learns Continually Rahul Ramesh, Pratik Chaudhari

NeurIPSW 2022 The Value of Out-of-Distribution Data Ashwin De Silva, Rahul Ramesh, Carey Priebe, Pratik Chaudhari, Joshua T Vogelstein

NeurIPSW 2021 Model Zoo: A Growing Brain That Learns Continually Rahul Ramesh, Pratik Chaudhari

ECML-PKDD 2020 Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning Arjun Manoharan, Rahul Ramesh, Balaraman Ravindran

IJCAI 2019 Successor Options: An Option Discovery Framework for Reinforcement Learning Rahul Ramesh, Manan Tomar, Balaraman Ravindran