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ORCIDRahul Singh 0002
Person information
- affiliation (PhD 2023): Georgia Institute of Technology, Atlanta, GA, USA
Other persons with the same name
- Rahul Singh — disambiguation page
- Rahul Singh 0001
![[0000-0003-0363-3666]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0003-0363-3666")
— Indian Institute of Science, Bengaluru, India (and 3 more) - Rahul Singh 0003 — Carnegie Mellon University, Pittsburgh, PA, USA
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2020 – today
- 2023
[b1]Rahul Singh:
Learning with graph structured data. Georgia Institute of Technology, Atlanta, GA, USA, 2023- [j7]Rahul Singh, Yongxin Chen:
Learning Gaussian Hidden Markov Models From Aggregate Data. IEEE Control. Syst. Lett. 7: 478-483 (2023) - [j6]Rahul Singh, Yongxin Chen:
Signed Graph Neural Networks: A Frequency Perspective. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j5]Rahul Singh, Qinsheng Zhang, Yongxin Chen:
Learning hidden Markov models from aggregate observations. Autom. 137: 110100 (2022) - [j4]Qinsheng Zhang, Rahul Singh, Yongxin Chen:
Inference of Aggregate Hidden Markov Models With Continuous Observations. IEEE Control. Syst. Lett. 6: 2377-2382 (2022) - [j3]Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen:
Inference With Aggregate Data in Probabilistic Graphical Models: An Optimal Transport Approach. IEEE Trans. Autom. Control. 67(9): 4483-4497 (2022) - [c6]Rahul Singh, Keuntaek Lee, Yongxin Chen:
Sample-based Distributional Policy Gradient. L4DC 2022: 676-688 - [i10]Rahul Singh, Yongxin Chen:
Signed Graph Neural Networks: A Frequency Perspective. CoRR abs/2208.07323 (2022) - 2021
- [j2]Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen:
Incremental Inference of Collective Graphical Models. IEEE Control. Syst. Lett. 5(2): 421-426 (2021) - [j1]Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen:
Multi-Marginal Optimal Transport and Probabilistic Graphical Models. IEEE Trans. Inf. Theory 67(7): 4647-4668 (2021) - [c5]Rahul Singh, Yongxin Chen:
Inference of collective Gaussian hidden Markov models. CDC 2021: 1637-1643 - [i9]Rahul Singh, Yongxin Chen:
Inference of collective Gaussian hidden Markov models. CoRR abs/2107.11662 (2021) - 2020
- [c4]Rahul Singh, Qinsheng Zhang, Yongxin Chen:
Improving Robustness via Risk Averse Distributional Reinforcement Learning. L4DC 2020: 958-968 - [i8]Rahul Singh, Keuntaek Lee, Yongxin Chen:
Sample-based Distributional Policy Gradient. CoRR abs/2001.02652 (2020) - [i7]Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen:
Inference with Aggregate Data: An Optimal Transport Approach. CoRR abs/2003.13933 (2020) - [i6]Rahul Singh, Qinsheng Zhang, Yongxin Chen:
Improving Robustness via Risk Averse Distributional Reinforcement Learning. CoRR abs/2005.00585 (2020) - [i5]Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen:
Multi-marginal optimal transport and probabilistic graphical models. CoRR abs/2006.14113 (2020) - [i4]Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen:
Incremental inference of collective graphical models. CoRR abs/2006.15035 (2020) - [i3]Qinsheng Zhang, Rahul Singh, Yongxin Chen:
Filtering for Aggregate Hidden Markov Models with Continuous Observations. CoRR abs/2011.02521 (2020) - [i2]Rahul Singh, Qinsheng Zhang, Yongxin Chen:
Learning Hidden Markov Models from Aggregate Observations. CoRR abs/2011.11236 (2020)
2010 – 2019
- 2019
- [c3]Songtao Lu, Rahul Singh, Xiangyi Chen, Yongxin Chen, Mingyi Hong:
Alternating Gradient Descent Ascent for Nonconvex Min-Max Problems in Robust Learning and GANs. ACSSC 2019: 680-684 - 2016
- [c2]Rahul Singh, Abhishek Chakraborty, B. S. Manoj:
On spectral analysis of node centralities. ANTS 2016: 1-5 - [c1]Rahul Singh, Abhishek Chakraborty, B. S. Manoj:
Graph Fourier transform based on directed Laplacian. SPCOM 2016: 1-5 - [i1]Rahul Singh, Abhishek Chakraborty, B. S. Manoj:
Graph Fourier Transform based on Directed Laplacian. CoRR abs/1601.03204 (2016)
Coauthor Index
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