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Jimmy T. H. Smith
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2020 – today
- 2024
- [c5]Sam Blouir, Jimmy T. H. Smith, Antonios Anastasopoulos, Amarda Shehu:
Birdie: Advancing State Space Language Modeling with Dynamic Mixtures of Training Objectives. EMNLP 2024: 9679-9705 - [c4]Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Michael Poli, Atsushi Yamashita:
State-Free Inference of State-Space Models: The *Transfer Function* Approach. ICML 2024 - [i7]Rom N. Parnichkun, Stefano Massaroli, Alessandro Moro, Jimmy T. H. Smith, Ramin M. Hasani, Mathias Lechner, Qi An, Christopher Ré, Hajime Asama, Stefano Ermon, Taiji Suzuki, Atsushi Yamashita, Michael Poli:
State-Free Inference of State-Space Models: The Transfer Function Approach. CoRR abs/2405.06147 (2024) - [i6]Jakub Smékal, Jimmy T. H. Smith, Michael Kleinman, Dan Biderman, Scott W. Linderman:
Towards a theory of learning dynamics in deep state space models. CoRR abs/2407.07279 (2024) - [i5]Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith, Scott W. Linderman:
Towards Scalable and Stable Parallelization of Nonlinear RNNs. CoRR abs/2407.19115 (2024) - [i4]Sam Blouir, Jimmy T. H. Smith, Antonios Anastasopoulos, Amarda Shehu:
Birdie: Advancing State Space Models with Reward-Driven Objectives and Curricula. CoRR abs/2411.01030 (2024) - 2023
- [c3]Jimmy T. H. Smith, Andrew Warrington, Scott W. Linderman:
Simplified State Space Layers for Sequence Modeling. ICLR 2023 - [c2]Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott W. Linderman, Wonmin Byeon:
Convolutional State Space Models for Long-Range Spatiotemporal Modeling. NeurIPS 2023 - [i3]Jimmy T. H. Smith, Shalini De Mello, Jan Kautz, Scott W. Linderman, Wonmin Byeon:
Convolutional State Space Models for Long-Range Spatiotemporal Modeling. CoRR abs/2310.19694 (2023) - 2022
- [i2]Jimmy T. H. Smith, Andrew Warrington, Scott W. Linderman:
Simplified State Space Layers for Sequence Modeling. CoRR abs/2208.04933 (2022) - 2021
- [c1]Jimmy T. H. Smith, Scott W. Linderman, David Sussillo:
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. NeurIPS 2021: 16700-16713 - [i1]Jimmy T. H. Smith, Scott W. Linderman, David Sussillo:
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems. CoRR abs/2111.01256 (2021)
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