Sarthak Mittal

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 23

Top Topics

Recurrent Neural Networks

Modular Architecture

Reinforcement Learning

Top Venues

Publications

Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos, Luca Scimeca, Jarrid Rector-Brooks, Alexandre Adam, Yoshua Bengio, Nikolay Malkin
On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling. CoRR (2024)
Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR (2024)
Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie
Does learning the right latent variables necessarily improve in-context learning? CoRR (2024)
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
Amortizing intractable inference in diffusion models for vision, language, and control. CoRR (2024)
Sarthak Mittal, Oleksii Hrinchuk, Oleksii Kuchaiev
Leveraging Synthetic Targets for Machine Translation. CoRR (2023)
Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi
MixupE: Understanding and improving Mixup from directional derivative perspective. UAI (2023)
Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou
Diffusion Based Representation Learning. ICML (2023)
Sarthak Mittal, Oleksii Hrinchuk, Oleksii Kuchaiev
Leveraging Synthetic Targets for Machine Translation. ACL (Findings) (2023)
Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
Is a Modular Architecture Enough? NeurIPS (2022)
Neetesh Kumar, Sarthak Mittal, Vaibhav Garg, Neeraj Kumar
Deep Reinforcement Learning-Based Traffic Light Scheduling Framework for SDN-Enabled Smart Transportation System. IEEE Trans. Intell. Transp. Syst. 23 (3) (2022)
Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou
From Points to Functions: Infinite-dimensional Representations in Diffusion Models. CoRR (2022)
Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
Is a Modular Architecture Enough? CoRR (2022)
Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective. CoRR (2022)
Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
Compositional Attention: Disentangling Search and Retrieval. ICLR (2022)
Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake A. Richards, Guillaume Lajoie
On Neural Architecture Inductive Biases for Relational Tasks. CoRR (2022)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks (2021)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR (2021)
Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
Compositional Attention: Disentangling Search and Retrieval. CoRR (2021)
Vaibhav Garg, Anuj Sachan, Neetesh Kumar, Sarthak Mittal
Congestion Control utilizing Software Defined Control Architecture at the Traffic Light Intersection. MASS (2021)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR (2020)
Anu Singh Lather, Ruchika Malhotra, Priya Saloni, Prabhjot Singh, Sarthak Mittal
Prediction of employee performance using machine learning techniques. AISS (2019)
Brady Neal, Sarthak Mittal, Aristide Baratin, Vinayak Tantia, Matthew Scicluna, Simon Lacoste-Julien, Ioannis Mitliagkas
A Modern Take on the Bias-Variance Tradeoff in Neural Networks. CoRR (2018)