Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems

Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems

19 July 2024

Scott W. Linderman

Papers citing "Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems"

19 / 19 papers shown

Title
Modeling Neural Activity with Conditionally Linear Dynamical Systems Victor Geadah Amin Nejatbakhsh David Lipshutz Jonathan W. Pillow Alex H. Williams AI4CE 180 0 0 25 Feb 2025
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs Kevin Course P. Nair 66 3 0 16 Dec 2023
Trainability, Expressivity and Interpretability in Gated Neural ODEs T. Kim T. Can K. Krishnamurthy AI4CE 60 5 0 12 Jul 2023
Variational Gaussian Process Diffusion Processes Prakhar Verma Vincent Adam Arno Solin DiffM 52 5 0 03 Jun 2023
Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics Noga Mudrik Yenho Chen Eva Yezerets Christopher Rozell Adam S. Charles 65 16 0 07 Jun 2022
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems Lukas Kohs Bastian Alt Heinz Koeppl 36 3 0 18 May 2022
Dual Parameterization of Sparse Variational Gaussian Processes Vincent Adam Paul E. Chang Mohammad Emtiyaz Khan Arno Solin 53 20 0 05 Nov 2021
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems Jimmy T.H. Smith Scott W. Linderman David Sussillo 70 28 0 01 Nov 2021
Variational Inference for Continuous-Time Switching Dynamical Systems Lukas Kohs Bastian Alt Heinz Koeppl 55 8 0 29 Sep 2021
Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories M. Genkin Owen K. Hughes Tatiana A. Engel 37 24 0 29 Dec 2020
Learning interpretable continuous-time models of latent stochastic dynamical systems Lea Duncker G. Bohner Julien Boussard M. Sahani 25 75 0 12 Feb 2019
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling Josue Nassar Scott W. Linderman M. Bugallo Il-Su Park AI4CE 28 73 0 29 Nov 2018
Empirical fixed point bifurcation analysis G. Bohner M. Sahani 25 3 0 04 Jul 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 288 5,024 0 19 Jun 2018
Identification of Gaussian Process State Space Models Stefanos Eleftheriadis Tom Nicholson M. Deisenroth J. Hensman 57 112 0 30 May 2017
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 211 4,748 0 04 Jan 2016
Expectation propagation for continuous time stochastic processes Botond Cseke David Schnoerr Manfred Opper G. Sanguinetti 40 19 0 18 Dec 2015
Black box variational inference for state space models Evan Archer Il Memming Park Lars Buesing John P. Cunningham Liam Paninski BDL 79 160 0 23 Nov 2015
Variational Gaussian Process State-Space Models R. Frigola Yutian Chen C. Rasmussen BDL 44 177 0 18 Jun 2014

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