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Sarthak Mittal
Sarthak Mittal
Mila, Université de Montréal
在 umontreal.ca 的电子邮件经过验证 - 首页
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A modern take on the bias-variance tradeoff in neural networks
B Neal, S Mittal, A Baratin, V Tantia, M Scicluna, S Lacoste-Julien, ...
arXiv preprint arXiv:1810.08591, 2018
2082018
Learning to combine top-down and bottom-up signals in recurrent neural networks with attention over modules
S Mittal, A Lamb, A Goyal, V Voleti, M Shanahan, G Lajoie, M Mozer, ...
International Conference on Machine Learning, 6972-6986, 2020
702020
Systematic evaluation of causal discovery in visual model based reinforcement learning
NR Ke, A Didolkar, S Mittal, A Goyal, G Lajoie, S Bauer, D Rezende, ...
NeurIPS 2021 Datasets and Benchmarks Track, 2021
392021
Is a modular architecture enough?
S Mittal, Y Bengio, G Lajoie
Advances in Neural Information Processing Systems 35, 28747-28760, 2022
342022
Diffusion-Based Representation Learning
S Mittal, K Abstreiter, S Bauer, B Schölkopf, A Mehrjou
International Conference on Machine Learning, 2023
24*2023
On neural architecture inductive biases for relational tasks
G Kerg, S Mittal, D Rolnick, Y Bengio, B Richards, G Lajoie
arXiv preprint arXiv:2206.05056, 2022
192022
Compositional Attention: Disentangling Search and Retrieval
S Mittal, SC Raparthy, I Rish, Y Bengio, G Lajoie
The International Conference on Learning Representations (ICLR), 2022, 2021
182021
A modern take on the bias-variance tradeoff in neural networks, 2019
B Neal, S Mittal, A Baratin, V Tantia, M Scicluna, S Lacoste-Julien, ...
URL https://openreview. net/forum, 1810
71810
From points to functions: Infinite-dimensional representations in diffusion models
S Mittal, G Lajoie, S Bauer, A Mehrjou
arXiv preprint arXiv:2210.13774, 2022
62022
On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling
M Sendera, M Kim, S Mittal, P Lemos, L Scimeca, J Rector-Brooks, ...
arXiv preprint arXiv:2402.05098, 2024
52024
MixupE: Understanding and improving Mixup from directional derivative perspective
Y Zou, V Verma, S Mittal, WH Tang, H Pham, J Kannala, Y Bengio, A Solin, ...
Uncertainty in Artificial Intelligence, 2597-2607, 2023
52023
A Modern Take on the Bias-Variance Tradeoff in Neural Networks.[arXiv]
B Neal, S Mittal, A Baratin, V Tantia, M Scicluna, S Lacoste-Julien, ...
arXiv preprint arXiv:1810.08591, 2019
52019
Inductive biases for relational tasks
G Kerg, S Mittal, D Rolnick, Y Bengio, BA Richards, G Lajoie
ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality, 2022
42022
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities
T Akhound-Sadegh, J Rector-Brooks, AJ Bose, S Mittal, P Lemos, CH Liu, ...
arXiv preprint arXiv:2402.06121, 2024
32024
Exploring Exchangeable Dataset Amortization for Bayesian Posterior Inference
S Mittal, NL Bracher, G Lajoie, P Jaini, MA Brubaker
ICML 2023 Workshop on Structured Probabilistic Inference {\&} Generative …, 2023
12023
Leveraging Synthetic Targets for Machine Translation
S Mittal, O Hrinchuk, O Kuchaiev
Findings of the Association for Computational Linguistics (2023), 2023
12023
Amortizing intractable inference in diffusion models for vision, language, and control
S Venkatraman, M Jain, L Scimeca, M Kim, M Sendera, M Hasan, L Rowe, ...
arXiv preprint arXiv:2405.20971, 2024
2024
Does learning the right latent variables necessarily improve in-context learning?
S Mittal, E Elmoznino, L Gagnon, S Bhardwaj, D Sridhar, G Lajoie
arXiv preprint arXiv:2405.19162, 2024
2024
Exchangeable Dataset Amortization for Bayesian Posterior Inference
S Mittal, NL Bracher, G Lajoie, P Jaini, MA Brubaker
2023
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