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LFADS - Latent Factor Analysis via Dynamical Systems

LFADS - Latent Factor Analysis via Dynamical Systems

22 August 2016
David Sussillo
Rafal Jozefowicz
L. F. Abbott
C. Pandarinath
    AI4CE
ArXivPDFHTML

Papers citing "LFADS - Latent Factor Analysis via Dynamical Systems"

9 / 9 papers shown
Title
Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors
Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors
Finn Schmidt
Suhas Shrinivasan
Polina Turishcheva
Fabian H. Sinz
37
0
0
21 Oct 2024
Diffusion-Based Generation of Neural Activity from Disentangled Latent
  Codes
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
23
1
0
30 Jul 2024
Latent Diffusion for Neural Spiking Data
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
Deep inference of latent dynamics with spatio-temporal super-resolution
  using selective backpropagation through time
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
21
10
0
29 Oct 2021
Representation learning for neural population activity with Neural Data
  Transformers
Representation learning for neural population activity with Neural Data Transformers
Joel Ye
C. Pandarinath
AI4TS
AI4CE
11
51
0
02 Aug 2021
Fitting summary statistics of neural data with a differentiable spiking
  network simulator
Fitting summary statistics of neural data with a differentiable spiking network simulator
G. Bellec
Shuqi Wang
Alireza Modirshanechi
Johanni Brea
W. Gerstner
31
11
0
18 Jun 2021
Recurrent switching linear dynamical systems
Recurrent switching linear dynamical systems
Scott W. Linderman
Andrew C. Miller
Ryan P. Adams
David M. Blei
Liam Paninski
Matthew J. Johnson
36
69
0
26 Oct 2016
Demixed principal component analysis of population activity in higher
  cortical areas reveals independent representation of task parameters
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parameters
D. Kobak
Wieland Brendel
C. Constantinidis
C. Feierstein
Adam Kepecs
Z. Mainen
R. Romo
Xue-Lian Qi
N. Uchida
C. Machens
42
464
0
22 Oct 2014
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
266
7,636
0
03 Jul 2012
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