The Riemannian Geometry of Deep Generative Models

21 November 2017

Papers citing "The Riemannian Geometry of Deep Generative Models"

50 / 103 papers shown

Title
Manifold Hypothesis in Data Analysis: Double Geometrically-Probabilistic Approach to Manifold Dimension Estimation A. Ivanov G. Nosovskiy A. Chekunov D. Fedoseev V. Kibkalo M. Nikulin Fedor Popelenskiy Stepan Alekseevich Komkov I. Mazurenko Aleksandr Petiushko 8 2 0 08 Jul 2021
On the Generative Utility of Cyclic Conditionals Chang-Shu Liu Haoyue Tang Tao Qin Jintao Wang Tie-Yan Liu 37 3 0 30 Jun 2021
Learning Identity-Preserving Transformations on Data Manifolds Marissa Connor Kion Fallah Christopher Rozell 32 6 0 22 Jun 2021
Manifold Matching via Deep Metric Learning for Generative Modeling Mengyu Dai Haibin Hang GAN 24 9 0 20 Jun 2021
Pulling back information geometry Georgios Arvanitidis Miguel González Duque Alison Pouplin Dimitris Kalatzis Søren Hauberg DRL 30 14 0 09 Jun 2021
Learning Riemannian Manifolds for Geodesic Motion Skills Hadi Beik-Mohammadi Søren Hauberg Georgios Arvanitidis Gerhard Neumann Leonel Rozo 29 33 0 08 Jun 2021
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder Clément Chadebec Elina Thibeau-Sutre Ninon Burgos S. Allassonnière 43 62 0 30 Apr 2021
Unsupervised Disentanglement of Linear-Encoded Facial Semantics Yutong Zheng Yu-Kai Huang R. Tao Zhiqiang Shen Marios Savvides CVBM DRL 31 12 0 30 Mar 2021
Atlas Generative Models and Geodesic Interpolation Jakob Stolberg-Larsen Stefan Sommer AI4CE 13 5 0 30 Jan 2021
Problems of representation of electrocardiograms in convolutional neural networks Iana Sereda Sergey Alekseev A. Koneva Alexey Khorkin Grigory V. Osipov 14 1 0 01 Dec 2020
S2FGAN: Semantically Aware Interactive Sketch-to-Face Translation Yan Yang Md Zakir Hossain Tom Gedeon Shafin Rahman CVBM 33 13 0 30 Nov 2020
Rethinking conditional GAN training: An approach using geometrically structured latent manifolds Sameera Ramasinghe M. Farazi Salman Khan Nick Barnes Stephen Gould GAN 37 8 0 25 Nov 2020
Learning a Deep Reinforcement Learning Policy Over the Latent Space of a Pre-trained GAN for Semantic Age Manipulation K. Shubham Gopalakrishnan Venkatesh Reijul Sachdev Akshi D. Jayagopi G. Srinivasaraghavan GAN 8 6 0 02 Nov 2020
Geometry-Aware Hamiltonian Variational Auto-Encoder Clément Chadebec Clément Mantoux S. Allassonnière DRL 24 15 0 22 Oct 2020
Learning Manifold Implicitly via Explicit Heat-Kernel Learning Yufan Zhou Changyou Chen Jinhui Xu 19 8 0 05 Oct 2020
Encoded Prior Sliced Wasserstein AutoEncoder for learning latent manifold representations Sanjukta Krishnagopal J. Bedrossian DRL 21 0 0 02 Oct 2020
Geometrically Enriched Latent Spaces Georgios Arvanitidis Søren Hauberg Bernhard Schölkopf DRL 19 51 0 02 Aug 2020
Fairwashing Explanations with Off-Manifold Detergent Christopher J. Anders Plamen Pasliev Ann-Kathrin Dombrowski K. Müller Pan Kessel FAtt FaML 21 94 0 20 Jul 2020
Manifolds for Unsupervised Visual Anomaly Detection Louise Naud Alexander Lavin DRL 13 6 0 19 Jun 2020
Variational Autoencoder with Learned Latent Structure Marissa Connor Gregory H. Canal Christopher Rozell CML DRL 29 42 0 18 Jun 2020
Sample complexity and effective dimension for regression on manifolds Andrew D. McRae Justin Romberg Mark A. Davenport 10 8 0 13 Jun 2020
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology Sharon Zhou E. Zelikman F. Lu A. Ng Gunnar Carlsson Stefano Ermon DRL 21 27 0 05 Jun 2020
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs Yujun Shen Ceyuan Yang Xiaoou Tang Bolei Zhou GAN CVBM 36 597 0 18 May 2020
Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation Marie-Julie Rakotosaona M. Ovsjanikov 3DPC 10 14 0 03 Apr 2020
Uniform Interpolation Constrained Geodesic Learning on Data Manifold Cong Geng Jia Wang Li Chen Wenbo Bao Chu Chu Zhiyong Gao 20 6 0 12 Feb 2020
On Implicit Regularization in $β$ -VAEs Abhishek Kumar Ben Poole DRL 26 53 0 31 Jan 2020
Disentangling Multiple Features in Video Sequences using Gaussian Processes in Variational Autoencoders Sarthak Bhagat Shagun Uppal Vivian Yin Nengli Lim DRL 8 2 0 08 Jan 2020
Representational Rényi heterogeneity Abraham Nunes M. Alda T. Bardouille Thomas Trappenberg 14 4 0 10 Dec 2019
Representing Closed Transformation Paths in Encoded Network Latent Space Marissa Connor Christopher Rozell 3DPC DRL 20 28 0 05 Dec 2019
Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders Nina Miolane S. Holmes DRL 19 20 0 19 Nov 2019
Interpreting the Latent Space of GANs for Semantic Face Editing Yujun Shen Jinjin Gu Xiaoou Tang Bolei Zhou CVBM GAN 60 1,115 0 25 Jul 2019
Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning Ankita Shukla Sarthak Bhagat Shagun Uppal Saket Anand Pavan Turaga CML OOD DRL 25 23 0 22 Jul 2019
Encoder-Powered Generative Adversarial Networks Jiseob Kim Seungjae Jung Hyun-Dong Lee Byoung-Tak Zhang GAN DRL 11 1 0 03 Jun 2019
Dimensionality compression and expansion in Deep Neural Networks Stefano Recanatesi M. Farrell Madhu S. Advani Timothy Moore Guillaume Lajoie E. Shea-Brown 26 72 0 02 Jun 2019
DeepFlow: History Matching in the Space of Deep Generative Models L. Mosser O. Dubrule M. Blunt 35 13 0 14 May 2019
Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models Lukasz Struski M. Sadowski Tomasz Danel Jacek Tabor Igor T. Podolak DiffM 28 7 0 06 Apr 2019
Geometry of Deep Generative Models for Disentangled Representations Ankita Shukla Shagun Uppal Sarthak Bhagat Saket Anand Pavan Turaga DRL 19 16 0 19 Feb 2019
Latent Space Cartography: Generalised Metric-Inspired Measures and Measure-Based Transformations for Generative Models M. Frenzel Bogdan Teleaga Asahi Ushio 8 7 0 06 Feb 2019
Latent Variable Modeling for Generative Concept Representations and Deep Generative Models Daniel T. Chang DRL BDL 12 4 0 26 Dec 2018
Adversarial Autoencoders with Constant-Curvature Latent Manifolds Daniele Grattarola L. Livi Cesare Alippi BDL 27 27 0 11 Dec 2018
Transferring Knowledge across Learning Processes Sebastian Flennerhag Pablo G. Moreno Neil D. Lawrence Andreas C. Damianou 21 64 0 03 Dec 2018
Intrinsic Universal Measurements of Non-linear Embeddings Ke Sun 13 0 0 05 Nov 2018
Point Cloud GAN Chun-Liang Li Manzil Zaheer Yang Zhang Barnabás Póczós Ruslan Salakhutdinov 3DPC 42 209 0 13 Oct 2018
The Deep Kernelized Autoencoder Michael C. Kampffmeyer Sigurd Løkse F. Bianchi Robert Jenssen L. Livi 11 18 0 19 Jul 2018
Manifold regularization with GANs for semi-supervised learning Bruno Lecouat Chuan-Sheng Foo Houssam Zenati V. Chandrasekhar GAN 24 14 0 11 Jul 2018
Only Bayes should learn a manifold (on the estimation of differential geometric structure from data) Søren Hauberg 16 31 0 13 Jun 2018
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization Bruno Lecouat Chuan-Sheng Foo Houssam Zenati V. Chandrasekhar GAN 30 29 0 23 May 2018
Latent Space Non-Linear Statistics Line Kühnel Tom Fletcher S. Joshi Stefan Sommer GAN DRL 13 34 0 19 May 2018
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds Daniele Grattarola Daniele Zambon Cesare Alippi L. Livi GNN 35 40 0 16 May 2018
Is Generator Conditioning Causally Related to GAN Performance? Augustus Odena Jacob Buckman Catherine Olsson Tom B. Brown C. Olah Colin Raffel Ian Goodfellow AI4CE 35 112 0 23 Feb 2018