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Inferring stochastic low-rank recurrent neural networks from neural data

24 June 2024

A Erdem Sağtekin

Jakob H Macke

Papers citing "Inferring stochastic low-rank recurrent neural networks from neural data"

24 / 24 papers shown

Title
True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics Christoph Jürgen Hemmer Daniel Durstewitz AI4TS SyDa AI4CE 288 1 0 19 May 2025
Modeling Neural Activity with Conditionally Linear Dynamical Systems Victor Geadah Amin Nejatbakhsh David Lipshutz Jonathan W. Pillow Alex H. Williams AI4CE 259 0 0 25 Feb 2025
Bifurcations and loss jumps in RNN training Lukas Eisenmann Zahra Monfared Niclas Alexander Göring Daniel Durstewitz 240 10 0 26 Oct 2023
Generalized Teacher Forcing for Learning Chaotic Dynamics Florian Hess Zahra Monfared Manuela Brenner Daniel Durstewitz AI4CE 228 35 0 07 Jun 2023
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers Johannes Zenn Robert Bamler 241 3 0 27 Apr 2023
Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto Samuel L. Smith Albert Gu Anushan Fernando Çağlar Gülçehre Razvan Pascanu Soham De 326 295 0 11 Mar 2023
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics Manuela Brenner Florian Hess G. Koppe Daniel Durstewitz 239 11 0 15 Dec 2022
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 264 32 0 06 Jul 2022
SIXO: Smoothing Inference with Twisted Objectives Dieterich Lawson Allan Raventós Andrew Warrington Scott W. Linderman BDL 240 15 0 13 Jun 2022
Long Expressive Memory for Sequence Modeling T. Konstantin Rusch Siddhartha Mishra N. Benjamin Erichson Michael W. Mahoney AI4TS 230 46 0 10 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 259 88 0 09 Sep 2021
Representation learning for neural population activity with Neural Data Transformers Joel Ye C. Pandarinath AI4TS AI4CE 221 54 0 02 Aug 2021
Continuous Latent Process Flows Ruizhi Deng Marcus A. Brubaker Greg Mori Andreas M. Lehrmann AI4TS 233 17 0 29 Jun 2021
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE Ding Zhou Xue-Xin Wei DRL 233 83 0 09 Nov 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 407 10,591 0 17 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 514 42,449 0 03 Dec 2019
On the Variance of the Adaptive Learning Rate and Beyond Liyuan Liu Haoming Jiang Pengcheng He Weizhu Chen Xiaodong Liu Jianfeng Gao Jiawei Han ODL 287 1,905 0 08 Aug 2019
Streaming Variational Monte Carlo Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 230 21 0 04 Jun 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 417 5,111 0 19 Jun 2018
Variational Sequential Monte Carlo C. A. Naesseth Scott W. Linderman Rajesh Ranganath David M. Blei BDL 263 214 0 31 May 2017
Auto-Encoding Sequential Monte Carlo T. Le Maximilian Igl Tom Rainforth Tom Jin Frank Wood BDL DRL 306 152 0 29 May 2017
Filtering Variational Objectives Chris J. Maddison Dieterich Lawson George Tucker N. Heess Mohammad Norouzi A. Mnih Arnaud Doucet Yee Whye Teh FedML 234 210 0 25 May 2017
A State Space Approach for Piecewise-Linear Recurrent Neural Networks for Reconstructing Nonlinear Dynamics from Neural Measurements Daniel Durstewitz 211 55 0 23 Dec 2016
Application of Girsanov Theorem to Particle Filtering of Discretely Observed Continuous-Time Non-Linear Systems Simo Särkkä T. Sottinen 502 46 0 11 May 2007