Explorations in Homeomorphic Variational Auto-Encoding

12 July 2018

Papers citing "Explorations in Homeomorphic Variational Auto-Encoding"

36 / 86 papers shown

Title
Continuous normalizing flows on manifolds Luca Falorsi BDL AI4CE 120 12 0 14 Mar 2021
Addressing the Topological Defects of Disentanglement via Distributed Operators Diane Bouchacourt Mark Ibrahim Stéphane Deny 128 22 0 10 Feb 2021
Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image ReconstructionIEEE International Symposium on Biomedical Imaging (ISBI), 2021 Koby Bibas Gili Weiss-Dicker Dana Cohen Noa Cahan H. Greenspan 142 8 0 10 Jan 2021
Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems Ryan Lopez P. Atzberger DRL AI4CE 213 12 0 07 Dec 2020
Joint Estimation of Image Representations and their Lie Invariants Christine Allen-Blanchette Kostas Daniilidis 155 0 0 05 Dec 2020
Learning Equivariant Representations Carlos Esteves BDL 154 0 0 04 Dec 2020
Generative Capacity of Probabilistic Protein Sequence ModelsNature Communications (Nat Commun), 2020 Francisco McGee Quentin Novinger R. Levy Vincenzo Carnevale A. Haldane 273 38 0 03 Dec 2020
What is a meaningful representation of protein sequences?Nature Communications (Nat Commun), 2020 N. Detlefsen Søren Hauberg Wouter Boomsma 451 136 0 28 Nov 2020
Deep Autoencoders: From Understanding to Generalization GuaranteesMathematical and Scientific Machine Learning (MSML), 2020 Romain Cosentino Randall Balestriero Richard Baraniuk B. Aazhang 179 6 0 20 Sep 2020
Manifolds for Unsupervised Visual Anomaly Detection Louise Naud Alexander Lavin DRL 171 7 0 19 Jun 2020
Neural Ordinary Differential Equations on Manifolds Luca Falorsi Patrick Forré BDL AI4CE 137 36 0 11 Jun 2020
The Power Spherical distribution Nicola De Cao Wilker Aziz 165 35 0 08 Jun 2020
Hyperbolic Manifold RegressionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Gian Maria Marconi Lorenzo Rosasco C. Ciliberto 171 7 0 28 May 2020
Disentanglement with Hyperspherical Latent Spaces using Diffusion Variational Autoencoders L. A. P. Rey DRL CoGe 62 5 0 19 Mar 2020
Stochastic Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2020 Hao Wu Jonas Köhler Frank Noé 429 203 0 16 Feb 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without SamplingInternational Conference on Machine Learning (ICML), 2020 Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud R. Zemel 217 14 0 13 Feb 2020
Variational Autoencoders with Riemannian Brownian Motion PriorsInternational Conference on Machine Learning (ICML), 2020 Dimitris Kalatzis David Eklund Georgios Arvanitidis Søren Hauberg BDL DRL 292 54 0 12 Feb 2020
Normalizing Flows on Tori and SpheresInternational Conference on Machine Learning (ICML), 2020 Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 258 171 0 06 Feb 2020
Chart Auto-Encoders for Manifold Structured Data Stefan C. Schonsheck Jie Chen Rongjie Lai DRL GNN 193 32 0 20 Dec 2019
No Representation without Transformation Giorgio Giannone Saeed Saremi Jonathan Masci Christian Osendorfer BDL DRL 136 2 0 09 Dec 2019
Representing Closed Transformation Paths in Encoded Network Latent SpaceAAAI Conference on Artificial Intelligence (AAAI), 2019 Marissa Connor Christopher Rozell 3DPC DRL 142 29 0 05 Dec 2019
A Neural Rendering Framework for Free-Viewpoint RelightingComputer Vision and Pattern Recognition (CVPR), 2019 Zhaoyu Chen Anpei Chen Guli Zhang Chengyuan Wang Yu Ji Kiriakos N. Kutulakos Jingyi Yu 279 50 0 26 Nov 2019
Variational Integrator Networks for Physically Structured EmbeddingsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 Steindór Sæmundsson Alexander Terenin Katja Hofmann M. Deisenroth GNN AI4CE 240 54 0 21 Oct 2019
Increasing Expressivity of a Hyperspherical VAE Tim R. Davidson Jakub M. Tomczak E. Gavves 129 6 0 07 Oct 2019
Explicitly disentangling image content from translation and rotation with spatial-VAENeural Information Processing Systems (NeurIPS), 2019 Tristan Bepler Ellen D. Zhong Kotaro Kelley E. Brignole Bonnie Berger CoGe DRL 122 81 0 25 Sep 2019
Deferred Neural Rendering: Image Synthesis using Neural TexturesACM Transactions on Graphics (TOG), 2019 Justus Thies Michael Zollhöfer Matthias Nießner 3DH 201 748 0 28 Apr 2019
Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres Shuai Liao E. Gavves Cees G. M. Snoek 178 71 0 10 Apr 2019
Semantics Preserving Adversarial Learning Ousmane Amadou Dia Elnaz Barshan Reza Babanezhad AAML GAN 386 2 0 10 Mar 2019
Reparameterizing Distributions on Lie Groups Luca Falorsi P. D. Haan Tim R. Davidson Patrick Forré BDL DRL 155 89 0 07 Mar 2019
Invariant-equivariant representation learning for multi-class dataInternational Conference on Machine Learning (ICML), 2019 Ilya Feige 134 10 0 08 Feb 2019
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders Emile Mathieu Charline Le Lan Chris J. Maddison Ryota Tomioka Yee Whye Teh BDL DRL 296 196 0 17 Jan 2019
Topological Constraints on Homeomorphic Auto-Encoding P. D. Haan Luca Falorsi 63 7 0 27 Dec 2018
On the Continuity of Rotation Representations in Neural Networks Yi Zhou Connelly Barnes Jingwan Lu Jimei Yang Hao Li 3DH 507 1,532 0 17 Dec 2018
Embedding-reparameterization procedure for manifold-valued latent variables in generative models Eugene Golikov M. Kretov DRL 101 0 0 06 Dec 2018
Cross-Domain 3D Equivariant Image Embeddings Carlos Esteves Avneesh Sud Zhengyi Luo Kostas Daniilidis A. Makadia 3DPC 177 23 0 06 Dec 2018
DeepVoxels: Learning Persistent 3D Feature Embeddings Vincent Sitzmann Justus Thies Felix Heide Matthias Nießner Gordon Wetzstein Michael Zollhöfer SSL 3DPC MDE 461 710 0 03 Dec 2018