Learning Wasserstein Embeddings

20 October 2017

Papers citing "Learning Wasserstein Embeddings"

22 / 22 papers shown

Title
Robust and Efficient Transfer Learning via Supernet Transfer in Warm-started Neural Architecture Search Prabhant Singh Joaquin Vanschoren AAML OOD 115 0 0 26 Jul 2024
CLAMS: A System for Zero-Shot Model Selection for Clustering Prabhant Singh Pieter Gijsbers Murat Onur Yildirim Elif Ceren Gok Joaquin Vanschoren 75 0 0 15 Jul 2024
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions Samantha Chen Yusu Wang 72 4 0 01 Aug 2023
Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation Peide Huang Mengdi Xu Jiacheng Zhu Laixi Shi Fei Fang Ding Zhao CLL 99 25 0 18 Oct 2022
Wasserstein Task Embedding for Measuring Task Similarities Xinran Liu Yikun Bai Yuzhe Lu Andrea Soltoggio Soheil Kolouri OT 83 25 0 24 Aug 2022
Neural Embedding: Learning the Embedding of the Manifold of Physics Data Sang Eon Park Philip C. Harris B. Ostdiek PINN DRL AI4CE 74 17 0 10 Aug 2022
Can Push-forward Generative Models Fit Multimodal Distributions? Antoine Salmona Valentin De Bortoli J. Delon A. Desolneux DiffM 85 39 0 29 Jun 2022
Meta Optimal Transport Brandon Amos Samuel N. Cohen Giulia Luise I. Redko OT 103 24 0 10 Jun 2022
SLOSH: Set LOcality Sensitive Hashing via Sliced-Wasserstein Embeddings Yuzhe Lu Xinran Liu Andrea Soltoggio Soheil Kolouri 84 8 0 11 Dec 2021
Learning Generalized Gumbel-max Causal Mechanisms Guy Lorberbom Daniel D. Johnson Chris J. Maddison Daniel Tarlow Tamir Hazan CML 72 20 0 11 Nov 2021
Learning to Generate Wasserstein Barycenters Julien Lacombe Julie Digne Nicolas Courty Nicolas Bonneel 57 12 0 24 Feb 2021
Central Limit Theorems for General Transportation Costs E. del Barrio Alberto González Sanz Jean-Michel Loubes OT 52 28 0 12 Feb 2021
Wasserstein Embedding for Graph Learning Soheil Kolouri Navid Naderializadeh Gustavo K. Rohde Heiko Hoffmann GNN 94 89 0 16 Jun 2020
PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation Noriaki Hirose Satoshi Koide Keisuke Kawano R. Kondo 69 7 0 03 Jun 2020
Deep Learning for Learning Graph Representations Wenwu Zhu Xin Eric Wang Peng Cui GNN AI4CE 50 23 0 02 Jan 2020
Learning transport cost from subset correspondence Ruishan Liu Akshay Balsubramani James Zou OT 54 14 0 29 Sep 2019
Interpretable ICD Code Embeddings with Self- and Mutual-Attention Mechanisms Dixin Luo Hongteng Xu Lawrence Carin 22 5 0 13 Jun 2019
Learning Embeddings into Entropic Wasserstein Spaces Charlie Frogner F. Mirzazadeh Justin Solomon 74 32 0 08 May 2019
2-Wasserstein Approximation via Restricted Convex Potentials with Application to Improved Training for GANs Amirhossein Taghvaei Amin Jalali 81 44 0 19 Feb 2019
An Entropic Optimal Transport Loss for Learning Deep Neural Networks under Label Noise in Remote Sensing Images B. Damodaran Rémi Flamary Vivien Seguy Nicolas Courty NoLa 63 40 0 02 Oct 2018
Distilled Wasserstein Learning for Word Embedding and Topic Modeling Hongteng Xu Wenlin Wang Wen Liu Lawrence Carin MedIm FedML 89 86 0 12 Sep 2018
BourGAN: Generative Networks with Metric Embeddings Chang Xiao Peilin Zhong Changxi Zheng GAN 88 69 0 19 May 2018