Siddharth Swaroop

According to our database, Siddharth Swaroop authored at least 20 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning.

Sarah Rathnam, Sonali Parbhoo, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez

J. Mach. Learn. Res., 2024

Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills.

Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Finale Doshi-Velez, Krzysztof Z. Gajos

CoRR, 2024

Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning.

Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Susan A. Murphy, Krzysztof Z. Gajos

CoRR, 2024

Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure.

Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, Finale Doshi-Velez

Proceedings of the 29th International Conference on Intelligent User Interfaces, 2024

Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks.

Eura Nofshin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

Differentially private partitioned variational inference.

Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela

Trans. Mach. Learn. Res., 2023

Improving Continual Learning by Accurate Gradient Reconstructions of the Past.

Erik A. Daxberger, Siddharth Swaroop, Kazuki Osawa, Rio Yokota, Richard E. Turner, José Miguel Hernández-Lobato, Mohammad Emtiyaz Khan

Trans. Mach. Learn. Res., 2023

Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning.

Lars Lien Ankile, Brian S. Ham, Kevin Mao, Eura Shin, Siddharth Swaroop, Finale Doshi-Velez, Weiwei Pan

CoRR, 2023

Adaptive interventions for both accuracy and time in AI-assisted human decision making.

Siddharth Swaroop, Zana Buçinca, Finale Doshi-Velez

CoRR, 2023

2022

Modeling Mobile Health Users as Reinforcement Learning Agents.

Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez

CoRR, 2022

Partitioned Variational Inference: A Framework for Probabilistic Federated Learning.

Matthew Ashman, Thang D. Bui, Cuong V. Nguyen, Efstratios Markou, Adrian Weller, Siddharth Swaroop, Richard E. Turner

CoRR, 2022

2021

Collapsed Variational Bounds for Bayesian Neural Networks.

Marcin Tomczak, Siddharth Swaroop, Andrew Y. K. Foong, Richard E. Turner

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Knowledge-Adaptation Priors.

Mohammad Emtiyaz Khan, Siddharth Swaroop

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generalized Variational Continual Learning.

Noel Loo, Siddharth Swaroop, Richard E. Turner

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Efficient Low Rank Gaussian Variational Inference for Neural Networks.

Marcin Tomczak, Siddharth Swaroop, Richard E. Turner

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Continual Deep Learning by Functional Regularisation of Memorable Past.

Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard E. Turner, Mohammad Emtiyaz Khan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Differentially Private Federated Variational Inference.

Mrinank Sharma, Michael J. Hutchinson, Siddharth Swaroop, Antti Honkela, Richard E. Turner

CoRR, 2019

Improving and Understanding Variational Continual Learning.

Siddharth Swaroop, Cuong V. Nguyen, Thang D. Bui, Richard E. Turner

CoRR, 2019

Practical Deep Learning with Bayesian Principles.

Kazuki Osawa, Siddharth Swaroop, Mohammad Emtiyaz Khan, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Partitioned Variational Inference: A unified framework encompassing federated and continual learning.

Thang D. Bui, Cuong V. Nguyen, Siddharth Swaroop, Richard E. Turner

CoRR, 2018