Sarthak Mittal

According to our database1, Sarthak Mittal authored at least 16 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.
CoRR, 2024

On diffusion models for amortized inference: Benchmarking and improving stochastic control and sampling.
CoRR, 2024

2023
MixupE: Understanding and improving Mixup from directional derivative perspective.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Diffusion Based Representation Learning.
Proceedings of the International Conference on Machine Learning, 2023

Leveraging Synthetic Targets for Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Deep Reinforcement Learning-Based Traffic Light Scheduling Framework for SDN-Enabled Smart Transportation System.
IEEE Trans. Intell. Transp. Syst., 2022

MixupE: Understanding and Improving Mixup from Directional Derivative Perspective.
CoRR, 2022

From Points to Functions: Infinite-dimensional Representations in Diffusion Models.
CoRR, 2022

On Neural Architecture Inductive Biases for Relational Tasks.
CoRR, 2022

Is a Modular Architecture Enough?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Compositional Attention: Disentangling Search and Retrieval.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Congestion Control utilizing Software Defined Control Architecture at the Traffic Light Intersection.
Proceedings of the IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems, 2021

2020
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Prediction of employee performance using machine learning techniques.
Proceedings of the AISS 2019: 2019 International Conference on Advanced Information Science and System, 2019

2018
A Modern Take on the Bias-Variance Tradeoff in Neural Networks.
CoRR, 2018


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