ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA

26 February 2020

Papers citing "ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA"

24 / 24 papers shown

Title
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research Patrik Reizinger Randall Balestriero David Klindt Wieland Brendel 83 0 0 17 Apr 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 70 3 0 16 Feb 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling Emanuele Marconato Sébastien Lachapelle Sebastian Weichwald Luigi Gresele 74 3 0 30 Oct 2024
Few-shot Domain Adaptation by Causal Mechanism Transfer Takeshi Teshima Issei Sato Masashi Sugiyama OOD CML TTA 40 86 0 10 Feb 2020
Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN) Peter Sorrenson Carsten Rother Ullrich Kothe DRL CML 20 119 0 14 Jan 2020
Flow Contrastive Estimation of Energy-Based Models Ruiqi Gao Erik Nijkamp Diederik P. Kingma Zhen Xu Andrew M. Dai Ying Nian Wu GAN 31 113 0 02 Dec 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 121 3,803 0 12 Jul 2019
Variational Autoencoders and Nonlinear ICA: A Unifying Framework Ilyes Khemakhem Diederik P. Kingma Ricardo Pio Monti Aapo Hyvarinen OOD 39 578 0 10 Jul 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 75 761 0 10 Jun 2019
Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA R. Monti Kun Zhang Aapo Hyvarinen CML 29 91 0 19 Apr 2019
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 80 1,451 0 29 Nov 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 175 3,110 0 09 Jul 2018
Conditional Noise-Contrastive Estimation of Unnormalised Models Ciwan Ceylan Michael U. Gutmann 33 42 0 10 Jun 2018
On gradient regularizers for MMD GANs Michael Arbel Danica J. Sutherland Mikolaj Binkowski Arthur Gretton 48 94 0 29 May 2018
A Unified Probabilistic Model for Learning Latent Factors and Their Connectivities from High-Dimensional Data R. Monti Aapo Hyvarinen 16 18 0 24 May 2018
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning Aapo Hyvarinen Hiroaki Sasaki Richard Turner OOD CML 64 318 0 22 May 2018
Deep Energy Estimator Networks Saeed Saremi Arash Mehrjou Bernhard Schölkopf Aapo Hyvarinen 34 73 0 21 May 2018
Understanding disentangling in $β$ -VAE Christopher P. Burgess I. Higgins Arka Pal Loic Matthey Nicholas Watters Guillaume Desjardins Alexander Lerchner CoGe DRL 32 828 0 10 Apr 2018
Structured Disentangled Representations Babak Esmaeili Hao Wu Sarthak Jain Alican Bozkurt N. Siddharth Brooks Paige Dana H. Brooks Jennifer Dy Jan-Willem van de Meent OOD CML BDL DRL 52 165 0 06 Apr 2018
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation Guosheng Lin Anton Milan Chunhua Shen Ian Reid AI4TS SSeg 205 2,835 0 20 Nov 2016
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA Aapo Hyvarinen H. Morioka CML OOD AI4TS 24 404 0 20 May 2016
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 216 4,143 0 21 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 385 149,474 0 22 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 310 16,972 0 20 Dec 2013