Mittal, Sarthak

18 publications

ICML 2025 Does Learning the Right Latent Variables Necessarily Improve In-Context Learning? Sarthak Mittal, Eric Elmoznino, Leo Gagnon, Sangnie Bhardwaj, Guillaume Lajoie, Dhanya Sridhar

ICML 2025 In-Context Learning and Occam’s Razor Eric Elmoznino, Tom Marty, Tejas Kasetty, Leo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie

ICML 2025 Learning Condensed Graph via Differentiable Atom Mapping for Reaction Yield Prediction Ankit Ghosh, Gargee Kashyap, Sarthak Mittal, Nupur Jain, Raghavan B Sunoj, Abir De

ICLR 2025 Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Pranam Chatterjee, Alexander Tong, Joey Bose

NeurIPS 2024 Amortizing Intractable Inference in Diffusion Models for Vision, Language, and Control Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin

ICLRW 2024 Explicit Knowledge Factorization Meets In-Context Learning: What Do We Gain? Sarthak Mittal, Eric Elmoznino, Leo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie

NeurIPS 2024 Improved Off-Policy Training of Diffusion Samplers Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin

ICML 2024 Iterated Denoising Energy Matching for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jarrid Rector-Brooks, Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

NeurIPSW 2024 Recurrent Interpolants for Probabilistic Time Series Prediction Yu Chen, Marin Biloš, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider

ICML 2023 Diffusion Based Representation Learning Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou

ICMLW 2023 Exploring Exchangeable Dataset Amortization for Bayesian Posterior Inference Sarthak Mittal, Niels Leif Bracher, Guillaume Lajoie, Priyank Jaini, Marcus A Brubaker

UAI 2023 MixupE: Understanding and Improving Mixup from Directional Derivative Perspective Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi

ICLR 2022 Compositional Attention: Disentangling Search and Retrieval Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie

ICLRW 2022 From Points to Functions: Infinite-Dimensional Representations in Diffusion Models Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou

ICLRW 2022 Inductive Biases for Relational Tasks Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake Aaron Richards, Guillaume Lajoie

NeurIPS 2022 Is a Modular Architecture Enough? Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie

ICML 2020 Learning to Combine Top-Down and Bottom-up Signals in Recurrent Neural Networks with Attention over Modules Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

ICMLW 2019 A Modern Take on the Bias-Variance Tradeoff in Neural Networks Brady Neal, Sarthak Mittal, Aristide Baratin, Vinayak Tantia, Matthew Scicluna, Simon Lacoste-Julien, Ioannis Mitliagkas