‪Jimmy T.H. Smith‬ - ‪Google Scholar‬

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	All	Since 2019
Citations	156	156
h-index	4	4
i10-index	2	2

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Co-authors

Scott LindermanStanford UniversityVerified email at stanford.edu
Andrew WarringtonPostdoc, Stanford UniversityVerified email at stanford.edu
David SussilloMeta Reality Labs and Adjunct Professor @ StanfordVerified email at stanford.edu
Dieterich LawsonStanford UniversityVerified email at stanford.edu

Jimmy T.H. Smith

Jimmy T.H. Smith

PhD student, Stanford

Verified email at stanford.edu

Machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Simplified state space layers for sequence modeling JTH Smith, A Warrington, SW Linderman arXiv preprint arXiv:2208.04933, 2022	130	2022
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems J Smith, S Linderman, D Sussillo Advances in Neural Information Processing Systems 34, 16700-16713, 2021	16	2021
Convolutional state space models for long-range spatiotemporal modeling J Smith, S De Mello, J Kautz, S Linderman, W Byeon Advances in Neural Information Processing Systems 36, 2024	5	2024
All-action policy gradient methods: A numerical integration approach B Petit, L Amdahl-Culleton, Y Liu, J Smith, PL Bacon arXiv preprint arXiv:1910.09093, 2019	5	2019
Bayesian Inference in Augmented Bow Tie Networks JTH Smith, D Lawson, SW Linderman

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Articles 1–5