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Sarthak Mittal
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2020 – today
- 2024
- [c10]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. ICML 2024 - [i16]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 abs/2402.05098 (2024) - [i15]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 abs/2402.06121 (2024) - [i14]Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie:
Does learning the right latent variables necessarily improve in-context learning? CoRR abs/2405.19162 (2024) - [i13]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 abs/2405.20971 (2024) - [i12]Yu Chen, Marin Bilos, Sarthak Mittal, Wei Deng, Kashif Rasul, Anderson Schneider:
Recurrent Interpolants for Probabilistic Time Series Prediction. CoRR abs/2409.11684 (2024) - [i11]Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng, Zachary Quinn, Cheng-Hao Liu, Sarthak Mittal, Nouha Dziri, Michael M. Bronstein, Yoshua Bengio, Pranam Chatterjee, Alexander Tong, Avishek Joey Bose:
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction. CoRR abs/2410.08134 (2024) - [i10]Eric Elmoznino, Tom Marty, Tejas Kasetty, Léo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie:
In-context learning and Occam's razor. CoRR abs/2410.14086 (2024) - 2023
- [c9]Sarthak Mittal, Oleksii Hrinchuk, Oleksii Kuchaiev:
Leveraging Synthetic Targets for Machine Translation. ACL (Findings) 2023: 9365-9379 - [c8]Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou:
Diffusion Based Representation Learning. ICML 2023: 24963-24982 - [c7]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: 2597-2607 - [i9]Sarthak Mittal, Oleksii Hrinchuk, Oleksii Kuchaiev:
Leveraging Synthetic Targets for Machine Translation. CoRR abs/2305.06155 (2023) - 2022
- [j1]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): 2411-2421 (2022) - [c6]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. ICLR 2022 - [c5]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? NeurIPS 2022 - [i8]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? CoRR abs/2206.02713 (2022) - [i7]Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake A. Richards, Guillaume Lajoie:
On Neural Architecture Inductive Biases for Relational Tasks. CoRR abs/2206.05056 (2022) - [i6]Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou:
From Points to Functions: Infinite-dimensional Representations in Diffusion Models. CoRR abs/2210.13774 (2022) - [i5]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 abs/2212.13381 (2022) - 2021
- [c4]Vaibhav Garg, Anuj Sachan, Neetesh Kumar, Sarthak Mittal:
Congestion Control utilizing Software Defined Control Architecture at the Traffic Light Intersection. MASS 2021: 597-602 - [c3]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 - [i4]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 abs/2107.00848 (2021) - [i3]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. CoRR abs/2110.09419 (2021) - 2020
- [c2]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: 6972-6986 - [i2]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 abs/2006.16981 (2020)
2010 – 2019
- 2019
- [c1]Anu Singh Lather, Ruchika Malhotra, Priya Saloni, Prabhjot Singh, Sarthak Mittal:
Prediction of employee performance using machine learning techniques. AISS 2019: 30:1-30:6 - 2018
- [i1]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 abs/1810.08591 (2018)
Coauthor Index
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last updated on 2024-11-28 21:28 CET by the dblp team
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