Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains

11 April 2016

Papers citing "Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains"

11 / 11 papers shown

Title
Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes Jonathan D. McCart Andrew R. Sedler Christopher Versteeg Domenick M. Mifsud Mattia Rigotti-Thompson C. Pandarinath DiffM SyDa 28 1 0 30 Jul 2024
Latent Diffusion for Neural Spiking Data J. Kapoor Auguste Schulz Julius Vetter Felix Pei Richard Gao Jakob H. Macke DiffM 38 2 0 27 Jun 2024
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics Matthew Dowling Yuan Zhao Il Memming Park BDL OffRL 21 6 0 18 May 2023
Compressed Predictive Information Coding Rui Meng Tianyi Luo K. Bouchard 24 1 0 03 Mar 2022
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time Feng Zhu Andrew R. Sedler Harrison A. Grier Nauman Ahad Mark A. Davenport Matthew T. Kaufman Andrea Giovannucci C. Pandarinath 27 10 0 29 Oct 2021
Nonnegative spatial factorization F. W. Townes Barbara E. Engelhardt 16 11 0 12 Oct 2021
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity Felix Pei Joel Ye D. Zoltowski Anqi Wu Raeed H. Chowdhury ... L. Miller Jonathan W. Pillow Il Memming Park Eva L. Dyer C. Pandarinath 50 87 0 09 Sep 2021
Representation learning for neural population activity with Neural Data Transformers Joel Ye C. Pandarinath AI4TS AI4CE 11 52 0 02 Aug 2021
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks Qi She Anqi Wu BDL 20 34 0 01 Jul 2019
LFADS - Latent Factor Analysis via Dynamical Systems David Sussillo Rafal Jozefowicz L. F. Abbott C. Pandarinath AI4CE 24 89 0 22 Aug 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 16 155 0 26 May 2016