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Adversarially-Contrastive Optimal Transport - ICML 2020 paper

Adversarially-Contrastive Optimal Transport - ICML 2020 paper

Optimal Transportation View of Generative Adversarial Networks

Optimal Transportation View of Generative Adversarial Networks

Model Compression Using Optimal Transport

Model Compression Using Optimal Transport

Contrastive Clustering with SwAV

Contrastive Clustering with SwAV

Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation

Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation

Multimodal Learning using Optimal Transport for Sarcasm and Humor Detection

Multimodal Learning using Optimal Transport for Sarcasm and Humor Detection

Keynote on Deep Declarative Networks with Application to Optimal Transport given at PRCV/DICTA 2022

Keynote on Deep Declarative Networks with Application to Optimal Transport given at PRCV/DICTA 2022

James Zou "Tutorial of optimal transport with applications in genomics"

James Zou "Tutorial of optimal transport with applications in genomics"

Aude Genevay (MIT) -- Learning with Sinkhorn divergences: from optimal transport to MMD

Aude Genevay (MIT) -- Learning with Sinkhorn divergences: from optimal transport to MMD

Self-Attention Message Passing for Contrastive Few-Shot Learning

Self-Attention Message Passing for Contrastive Few-Shot Learning

Fast Sinkhorn Filters (CVPR 2021)

Fast Sinkhorn Filters (CVPR 2021)

Least Squares GANs | Lecture 67 (Part 1) | Applied Deep Learning

Least Squares GANs | Lecture 67 (Part 1) | Applied Deep Learning

Tias Guns - Prediction + Optimisation: without and with decision-focused learning - IPAM at UCLA

Tias Guns - Prediction + Optimisation: without and with decision-focused learning - IPAM at UCLA

Adaptive Inducing Point Selection for Gaussian Processes -Workshop Continual Learning - ICML 2020

Adaptive Inducing Point Selection for Gaussian Processes -Workshop Continual Learning - ICML 2020

[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

Stanford CS330 Deep Multi-Task & Meta Learning - Domain Adaptation l 2022 I Lecture 13

Stanford CS330 Deep Multi-Task & Meta Learning - Domain Adaptation l 2022 I Lecture 13

Optimal Continual Learning has Perfect Memory and is NP hard

Optimal Continual Learning has Perfect Memory and is NP hard

[ICCV 2021] InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images

[ICCV 2021] InSeGAN: A Generative Approach to Segmenting Identical Instances in Depth Images

Learning with Noisy Labels - Dr. Tongliang Liu

Learning with Noisy Labels - Dr. Tongliang Liu

GeoDA: a geometric framework for black-box adversarial attacks

GeoDA: a geometric framework for black-box adversarial attacks

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