147 citations · 719 across the 43 of their papers we have counts for
5 papers · 1 filter
Brain-to-Text Benchmark '24: Lessons Learned
Francis R. Willett, Jingyuan Li, Trung Le +13
Speech brain-computer interfaces aim to decipher what a person is trying to say from neural activity alone, restoring communication to people with paralysis who have lost the abili…
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems
Amber Hu, David Zoltowski, Aditya Nair +3
Understanding how the collective activity of neural populations relates to computation and ultimately behavior is a key goal in neuroscience. To this end, statistical methods which…
Towards a theory of learning dynamics in deep state space models
Jakub Smékal, Jimmy T. H. Smith, Michael Kleinman +2
State space models (SSMs) have shown remarkable empirical performance on many long sequence modeling tasks, but a theoretical understanding of these models is still lacking. In thi…
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Feng Chen +3
Discrete diffusion has emerged as a powerful framework for generative modeling in discrete domains, yet efficiently sampling from these models remains challenging. Existing samplin…
Towards Scalable and Stable Parallelization of Nonlinear RNNs
Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith +1
Transformers and linear state space models can be evaluated in parallel on modern hardware, but evaluating nonlinear RNNs appears to be an inherently sequential problem. Recently,…