Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles

6 October 2022

Papers citing "Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles"

7 / 7 papers shown

Title
Modeling Dynamic Neural Activity by combining Naturalistic Video Stimuli and Stimulus-independent Latent Factors Finn Schmidt Suhas Shrinivasan Polina Turishcheva Fabian H. Sinz 145 1 0 21 Oct 2024
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
Towards robust vision by multi-task learning on monkey visual cortex Shahd Safarani Arne F. Nix K. Willeke Santiago A. Cadena Kelli Restivo George H. Denfield A. Tolias Fabian H. Sinz OOD 56 53 0 29 Jul 2021
Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAE Ding Zhou Xue-Xin Wei DRL 233 81 0 09 Nov 2020
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA Ilyes Khemakhem R. Monti Diederik P. Kingma Aapo Hyvarinen CML 69 114 0 26 Feb 2020
On the Continuity of Rotation Representations in Neural Networks Yi Zhou Connelly Barnes Jingwan Lu Jimei Yang Hao Li 3DH 73 1,289 0 17 Dec 2018
Hyperspherical Variational Auto-Encoders Tim R. Davidson Luca Falorsi Nicola De Cao Thomas Kipf Jakub M. Tomczak DRL BDL 104 384 0 03 Apr 2018