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Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks

Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks

1 July 2019
Qi She
Anqi Wu
    BDL
ArXivPDFHTML

Papers citing "Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks"

15 / 15 papers shown
Title
When predict can also explain: few-shot prediction to select better neural latents
When predict can also explain: few-shot prediction to select better neural latents
Kabir Dabholkar
Omri Barak
BDL
57
0
0
23 May 2024
Bayesian Non-linear Latent Variable Modeling via Random Fourier Features
Bayesian Non-linear Latent Variable Modeling via Random Fourier Features
M. Zhang
Gregory W. Gundersen
Barbara Engelhardt
BDL
16
2
0
14 Jun 2023
Compressed Predictive Information Coding
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
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
Neural Latents Benchmark '21: Evaluating latent variable models of
  neural population activity
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
Representation learning for neural population activity with Neural Data Transformers
Joel Ye
C. Pandarinath
AI4TS
AI4CE
11
52
0
02 Aug 2021
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal
  Stochastic Linear Mixing Model
Bayesian Inference in High-Dimensional Time-Serieswith the Orthogonal Stochastic Linear Mixing Model
Rui Meng
K. Bouchard
AI4TS
24
2
0
25 Jun 2021
Deep Probabilistic Time Series Forecasting using Augmented Recurrent
  Input for Dynamic Systems
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems
Haitao Liu
Changjun Liu
Xiaomo Jiang
Xudong Chen
Shuhua Yang
Xiaofang Wang
BDL
AI4TS
44
2
0
03 Jun 2021
Building population models for large-scale neural recordings:
  opportunities and pitfalls
Building population models for large-scale neural recordings: opportunities and pitfalls
C. Hurwitz
N. Kudryashova
A. Onken
Matthias H Hennig
20
39
0
03 Feb 2021
IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object
  Recognition Report
IROS 2019 Lifelong Robotic Vision Challenge -- Lifelong Object Recognition Report
Qi She
Fan Feng
Qi Liu
Rosa H. M. Chan
Xinyue Hao
...
Di Xie
Yangsheng Xu
Lin Yang
Qiaoyong Zhong
Liguang Zhou
6
2
0
26 Apr 2020
CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture
  Recognition
CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition
Zhengwei Wang
Qi She
Tejo Chalasani
A. Smolic
3DPC
SLR
21
15
0
20 Apr 2020
A Neuro-AI Interface for Evaluating Generative Adversarial Networks
A Neuro-AI Interface for Evaluating Generative Adversarial Networks
Zhengwei Wang
Qi She
Alan F. Smeaton
T. Ward
Graham Healy
EGVM
13
2
0
05 Mar 2020
OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong
  Deep Learning
OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep Learning
Qi She
Fan Feng
Xinyue Hao
Qihan Yang
Chuanlin Lan
...
Zhengwei Wang
Yao Guo
Yimin Zhang
Fei Qiao
Rosa H. M. Chan
VLM
38
75
0
15 Nov 2019
A Spectral Nonlocal Block for Neural Networks
A Spectral Nonlocal Block for Neural Networks
Lei Zhu
Qi She
Lidan Zhang
Ping Guo
18
2
0
04 Nov 2019
An Efficient and Flexible Spike Train Model via Empirical Bayes
An Efficient and Flexible Spike Train Model via Empirical Bayes
Qi She
Xiaoli Wu
Beth Jelfs
Adam S. Charles
Rosa H.M.Chan
19
0
0
10 May 2016
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