Shantanu Thakoor

According to our database1, Shantanu Thakoor authored at least 17 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
Gemma 2: Improving Open Language Models at a Practical Size.
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CoRR, 2024

2023
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Self-Predictive Learning for Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition.
Proceedings of the International Conference on Machine Learning, 2023

Half-Hop: A graph upsampling approach for slowing down message passing.
Proceedings of the International Conference on Machine Learning, 2023

2022
Learning Behavior Representations Through Multi-Timescale Bootstrapping.
CoRR, 2022

BYOL-Explore: Exploration by Bootstrapped Prediction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generalised Policy Improvement with Geometric Policy Composition.
Proceedings of the International Conference on Machine Learning, 2022

Large-Scale Representation Learning on Graphs via Bootstrapping.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Quantifying and Understanding Adversarial Examples in Discrete Input Spaces.
CoRR, 2021

Large-scale graph representation learning with very deep GNNs and self-supervision.
CoRR, 2021

Bootstrapped Representation Learning on Graphs.
CoRR, 2021

Geometric Entropic Exploration.
CoRR, 2021

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Counterfactual Credit Assignment in Model-Free Reinforcement Learning.
CoRR, 2020

2019
The Marabou Framework for Verification and Analysis of Deep Neural Networks.
Proceedings of the Computer Aided Verification - 31st International Conference, 2019

2018
Synthesis of Programs from Multimodal Datasets.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018


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