Reparameterizing Distributions on Lie Groups

7 March 2019

Papers citing "Reparameterizing Distributions on Lie Groups"

23 / 23 papers shown

Title
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups Yuchen Zhu Tianrong Chen Lingkai Kong Evangelos A. Theodorou Molei Tao DiffM 48 5 0 25 May 2024
A Metric-based Principal Curve Approach for Learning One-dimensional Manifold E. Cui 18 0 0 20 May 2024
Latent Space Symmetry Discovery Jianke Yang Nima Dehmamy Robin Walters Rose Yu 42 12 0 29 Sep 2023
Rigid Body Flows for Sampling Molecular Crystal Structures Jonas Köhler Michele Invernizzi P. D. Haan Frank Noé AI4CE 46 27 0 26 Jan 2023
The Neural Process Family: Survey, Applications and Perspectives Saurav Jha Dong Gong Xuesong Wang Richard Turner L. Yao BDL 83 24 0 01 Sep 2022
Generalized Normalizing Flows via Markov Chains Paul Hagemann J. Hertrich Gabriele Steidl BDL DiffM AI4CE 30 22 0 24 Nov 2021
Learning Partial Equivariances from Data David W. Romero Suhas Lohit 23 28 0 19 Oct 2021
Moser Flow: Divergence-based Generative Modeling on Manifolds N. Rozen Aditya Grover Maximilian Nickel Y. Lipman DRL AI4CE 27 57 0 18 Aug 2021
Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold Kieran A. Murphy Carlos Esteves Varun Jampani Srikumar Ramalingam A. Makadia 20 76 0 10 Jun 2021
Continuous normalizing flows on manifolds Luca Falorsi BDL AI4CE 30 10 0 14 Mar 2021
Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation Haowen Deng Mai Bui Nassir Navab Leonidas J. Guibas Slobodan Ilic Tolga Birdal 3DH 28 58 0 20 Dec 2020
Riemannian Continuous Normalizing Flows Emile Mathieu Maximilian Nickel AI4CE 27 119 0 18 Jun 2020
Variational Autoencoder with Learned Latent Structure Marissa Connor Gregory H. Canal Christopher Rozell CML DRL 34 42 0 18 Jun 2020
Neural Manifold Ordinary Differential Equations Aaron Lou Derek Lim Isay Katsman Leo Huang Qingxuan Jiang Ser-Nam Lim Christopher De Sa BDL AI4CE 23 79 0 18 Jun 2020
Manifold GPLVMs for discovering non-Euclidean latent structure in neural data Kristopher T. Jensen Ta-Chu Kao Marco Tripodi Guillaume Hennequin DRL 22 31 0 12 Jun 2020
The Power Spherical distribution Nicola De Cao Wilker Aziz 24 28 0 08 Jun 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Normalizing Flows on Tori and Spheres Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 18 153 0 06 Feb 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 67 1,635 0 05 Dec 2019
Increasing Expressivity of a Hyperspherical VAE Tim R. Davidson Jakub M. Tomczak E. Gavves 13 6 0 07 Oct 2019
The Functional Neural Process Christos Louizos Xiahan Shi Klamer Schutte Max Welling BDL 38 77 0 19 Jun 2019
A RAD approach to deep mixture models Laurent Dinh Jascha Narain Sohl-Dickstein Hugo Larochelle Razvan Pascanu 22 45 0 18 Mar 2019
Stochastic Backpropagation through Mixture Density Distributions Alex Graves BDL 57 44 0 19 Jul 2016