I am a PhD student in computational math (ICME) at Stanford University, advised by Scott Linderman. My research interests are broadly related to combining state space models and deep learning approaches to improve sequence modeling. Before Stanford, I obtained a master’s degree at MIT in the LGO program and attended undergrad at Georgia Tech.
Simplified State Space Layers for Sequence Modeling
Jimmy T.H. Smith, Andrew Warrington, Scott W. Linderman
International Conference on Learning Representations (ICLR) 2023. Selected for Oral Presentation (top 5% of accepted papers, top 1.5% of all submissions)
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems
Jimmy T.H. Smith, Scott W. Linderman, David Sussillo
Advances in Neural Information Processing Systems (NeurIPS) 2021.
Bayesian Inference in Augmented Bow Tie Networks
Jimmy T.H. Smith, Dieterich Lawson, Scott W. Linderman
Bayesian Deep Learning Workshop, NeurIPS 2021.