Rahul Singh - RankMe

24 papers Misc 1Journal 17Unranked 5

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Learning Gaussian Hidden Markov Models From Aggregate Data. IEEE Control. Syst. Lett. Rahul Singh, Yongxin Chen
2023	—	`—`	Learning with graph structured data. Rahul Singh
2023	J	`jnl`	Signed Graph Neural Networks: A Frequency Perspective. Trans. Mach. Learn. Res. Rahul Singh, Yongxin Chen
2022	J	`jnl`	Inference With Aggregate Data in Probabilistic Graphical Models: An Optimal Transport Approach. IEEE Trans. Autom. Control. Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2022	J	`jnl`	Inference of Aggregate Hidden Markov Models With Continuous Observations. IEEE Control. Syst. Lett. Qinsheng Zhang, Rahul Singh, Yongxin Chen
2022	J	`jnl`	Learning hidden Markov models from aggregate observations. Autom. Rahul Singh, Qinsheng Zhang, Yongxin Chen
2022	—	`conf`	Sample-based Distributional Policy Gradient. L4DC Rahul Singh, Keuntaek Lee, Yongxin Chen
2022	J	`jnl`	Signed Graph Neural Networks: A Frequency Perspective. CoRR Rahul Singh, Yongxin Chen
2021	J	`jnl`	Incremental Inference of Collective Graphical Models. IEEE Control. Syst. Lett. Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2021	—	`conf`	Inference of collective Gaussian hidden Markov models. CDC Rahul Singh, Yongxin Chen
2021	J	`jnl`	Inference of collective Gaussian hidden Markov models. CoRR Rahul Singh, Yongxin Chen
2021	J	`jnl`	Multi-Marginal Optimal Transport and Probabilistic Graphical Models. IEEE Trans. Inf. Theory Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2020	J	`jnl`	Filtering for Aggregate Hidden Markov Models with Continuous Observations. CoRR Qinsheng Zhang, Rahul Singh, Yongxin Chen
2020	—	`conf`	Improving Robustness via Risk Averse Distributional Reinforcement Learning. L4DC Rahul Singh, Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Improving Robustness via Risk Averse Distributional Reinforcement Learning. CoRR Rahul Singh, Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Incremental inference of collective graphical models. CoRR Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2020	J	`jnl`	Inference with Aggregate Data: An Optimal Transport Approach. CoRR Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2020	J	`jnl`	Learning Hidden Markov Models from Aggregate Observations. CoRR Rahul Singh, Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Multi-marginal optimal transport and probabilistic graphical models. CoRR Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2020	J	`jnl`	Sample-based Distributional Policy Gradient. CoRR Rahul Singh, Keuntaek Lee, Yongxin Chen
2019	Misc	`conf`	Alternating Gradient Descent Ascent for Nonconvex Min-Max Problems in Robust Learning and GANs. ACSSC Songtao Lu, Rahul Singh, Xiangyi Chen, Yongxin Chen, Mingyi Hong
2016	J	`jnl`	Graph Fourier Transform based on Directed Laplacian. CoRR Rahul Singh, Abhishek Chakraborty, B. S. Manoj
2016	—	`conf`	Graph Fourier transform based on directed Laplacian. SPCOM Rahul Singh, Abhishek Chakraborty, B. S. Manoj
2016	—	`conf`	On spectral analysis of node centralities. ANTS Rahul Singh, Abhishek Chakraborty, B. S. Manoj