Rahul Singh

According to our database, Rahul Singh authored at least 14 papers between 2019 and 2023.

Collaborative distances:

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

2023

Learning with graph structured data.

Rahul Singh

PhD thesis, 2023

Signed Graph Neural Networks: A Frequency Perspective.

Rahul Singh, Yongxin Chen

Trans. Mach. Learn. Res., 2023

Learning Gaussian Hidden Markov Models From Aggregate Data.

Rahul Singh, Yongxin Chen

IEEE Control. Syst. Lett., 2023

2022

Inference With Aggregate Data in Probabilistic Graphical Models: An Optimal Transport Approach.

Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen

IEEE Trans. Autom. Control., 2022

Inference of Aggregate Hidden Markov Models With Continuous Observations.

Qinsheng Zhang, Rahul Singh, Yongxin Chen

IEEE Control. Syst. Lett., 2022

Learning hidden Markov models from aggregate observations.

Rahul Singh, Qinsheng Zhang, Yongxin Chen

Autom., 2022

Sample-based Distributional Policy Gradient.

Rahul Singh, Keuntaek Lee, Yongxin Chen

Proceedings of the Learning for Dynamics and Control Conference, 2022

2021

Multi-Marginal Optimal Transport and Probabilistic Graphical Models.

Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen

IEEE Trans. Inf. Theory, 2021

Incremental Inference of Collective Graphical Models.

Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen

IEEE Control. Syst. Lett., 2021

Inference of collective Gaussian hidden Markov models.

Rahul Singh, Yongxin Chen

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Filtering for Aggregate Hidden Markov Models with Continuous Observations.

Qinsheng Zhang, Rahul Singh, Yongxin Chen

CoRR, 2020

Inference with Aggregate Data: An Optimal Transport Approach.

Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen

CoRR, 2020

Improving Robustness via Risk Averse Distributional Reinforcement Learning.

Rahul Singh, Qinsheng Zhang, Yongxin Chen

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

2019

Alternating Gradient Descent Ascent for Nonconvex Min-Max Problems in Robust Learning and GANs.

Songtao Lu, Rahul Singh, Xiangyi Chen, Yongxin Chen, Mingyi Hong

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019