Gupta, Gunshi

12 publications

NeurIPS 2025 Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning Gunshi Gupta, Karmesh Yadav, Zsolt Kira, Yarin Gal, Rahaf Aljundi

NeurIPS 2025 Recurrent Attention-Based Token Selection for Efficient Streaming Video-LLMs Vaggelis Dorovatas, Soroush Seifi, Gunshi Gupta, Rahaf Aljundi

NeurIPS 2024 Pre-Trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control Gunshi Gupta, Karmesh Yadav, Yarin Gal, Zsolt Kira, Dhruv Batra, Cong Lu, Tim G. J. Rudner

ICLRW 2024 Pre-Trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control Gunshi Gupta, Karmesh Yadav, Yarin Gal, Dhruv Batra, Zsolt Kira, Cong Lu, Tim G. J. Rudner

ICML 2024 ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages Andrew Jesson, Chris Lu, Gunshi Gupta, Nicolas Beltran-Velez, Angelos Filos, Jakob Nicolaus Foerster, Yarin Gal

CLeaR 2023 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal

NeurIPSW 2022 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal

NeurIPSW 2022 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal

NeurIPSW 2022 Can Active Sampling Reduce Causal Confusion in Offline Reinforcement Learning? Gunshi Gupta, Tim G. J. Rudner, Rowan Thomas McAllister, Adrien Gaidon, Yarin Gal

ICMLW 2020 La-MAML: Look-Ahead Meta Learning for Continual Learning Gunshi Gupta, Karmesh Yadav, Liam Paull

NeurIPS 2020 Look-Ahead Meta Learning for Continual Learning Gunshi Gupta, Karmesh Yadav, Liam Paull

CVPRW 2018 Geometric Consistency for Self-Supervised End-to-End Visual Odometry Ganesh Iyer, J. Krishna Murthy, Gunshi Gupta, K. Madhava Krishna, Liam Paull