Mon 5:00 a.m. - 5:45 a.m.
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Optimal Transport in the Biomedical Sciences: Challenges and Opportunities
(
Plenary talk
)
>
SlidesLive Video
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Caroline Uhler
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Mon 5:45 a.m. - 6:00 a.m.
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Implicit Riemannian Concave Potential Maps
(
Oral
)
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SlidesLive Video
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Danilo Jimenez Rezende · Sébastien Racanière
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Mon 6:00 a.m. - 7:10 a.m.
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Regularity theory of optimal transport maps
(
Plenary talk
)
>
SlidesLive Video
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Alessio Figalli
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Mon 7:10 a.m. - 7:35 a.m.
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Generative adversarial learning with adapted distances
(
Keynote talk
)
>
SlidesLive Video
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Beatrice Acciaio
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Mon 7:35 a.m. - 8:15 a.m.
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Spotlight Presentations
(
Spotlight Presentations
)
>
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Mon 8:15 a.m. - 8:45 a.m.
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Poster Session
(
Poster Session
)
>
link
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🔗
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Mon 8:45 a.m. - 9:30 a.m.
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Entropic Regularization of Optimal Transport as a Statistical Regularization
(
Plenary talk
)
>
SlidesLive Video
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Lénaïc Chizat
🔗
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Mon 9:30 a.m. - 9:55 a.m.
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Optimal transport and probability flows
(
Keynote talk
)
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SlidesLive Video
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Chin-Wei Huang
🔗
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Mon 9:55 a.m. - 10:20 a.m.
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Graphical Optimal Transport and its applications
(
Keynote talk
)
>
SlidesLive Video
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Yongxin Chen
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Mon 10:20 a.m. - 11:00 a.m.
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Poster Session
(
Poster Session
)
>
link
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🔗
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Mon 11:00 a.m. - 11:25 a.m.
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Enabling integrated analysis of single-cell multi-omic datasets with optimal transport
(
Keynote talk
)
>
SlidesLive Video
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Pinar Demetci
🔗
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Mon 11:25 a.m. - 11:40 a.m.
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Entropic estimation of optimal transport maps
(
Oral
)
>
SlidesLive Video
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Aram-Alexandre Pooladian · Jonathan Niles-Weed
🔗
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Mon 11:40 a.m. - 11:55 a.m.
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Discrete Schrödinger Bridges with Applications to Two-Sample Homogeneity Testing
(
Oral
)
>
SlidesLive Video
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Zaid Harchaoui · Lang Liu · Soumik Pal
🔗
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Mon 11:55 a.m. - 12:20 p.m.
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Benefits of using optimal transport in computational learning and inversion
(
Keynote talk
)
>
SlidesLive Video
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Yunan Yang
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Mon 12:20 p.m. - 12:25 p.m.
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Concluding Remarks
(
Discussion
)
>
SlidesLive Video
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Mon 12:25 p.m. - 1:00 p.m.
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Poster session - 3 and social interaction
(
Poster session
)
>
link
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🔗
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-
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Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe
(
Poster
)
>
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Thibault Sejourne · Francois-Xavier Vialard · Gabriel Peyré
🔗
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-
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Faster Unbalanced Optimal Transport: Translation invariant Sinkhorn and 1-D Frank-Wolfe
(
Spotlight
)
>
SlidesLive Video
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Thibault Sejourne · Francois-Xavier Vialard · Gabriel Peyré
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-
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Linear Convergence of Batch Greenkhorn for Regularized Multimarginal Optimal Transport
(
Poster
)
>
link
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Vladimir Kostic · Saverio Salzo · Massimiliano Pontil
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-
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Gradient flows on graphons: existence, convergence, continuity equations
(
Poster
)
>
link
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Sewoong Oh · Soumik Pal · Raghav Somani · Raghav Tripathi
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-
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Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
(
Poster
)
>
link
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Meyer Scetbon · Gabriel Peyré · Marco Cuturi
🔗
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-
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Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
(
Spotlight
)
>
link
SlidesLive Video
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Meyer Scetbon · Gabriel Peyré · Marco Cuturi
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-
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Cross-Domain Lossy Compression as Optimal Transport with an Entropy Bottleneck
(
Poster
)
>
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Huan Liu · George Zhang · Jun Chen · Ashish Khisti
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-
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Learning Single-Cell Perturbation Responses using Neural Optimal Transport
(
Poster
)
>
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Charlotte Bunne · Stefan Stark · Gabriele Gut · Andreas Krause · Gunnar Rätsch · Lucas Pelkmans · Kjong Lehmann
🔗
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-
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Input Convex Gradient Networks
(
Poster
)
>
link
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Jack Richter-Powell · Jonathan Lorraine · Brandon Amos
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-
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Input Convex Gradient Networks
(
Spotlight
)
>
link
SlidesLive Video
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Jack Richter-Powell · Jonathan Lorraine · Brandon Amos
🔗
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-
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On the complexity of the optimal transport problem with graph-structured cost
(
Poster
)
>
link
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Jiaojiao Fan · Isabel Haasler · Johan Karlsson · Yongxin Chen
🔗
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-
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Subspace Detours Meet Gromov-Wasserstein
(
Poster
)
>
link
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Clément Bonet · Nicolas Courty · François Septier · Lucas Drumetz
🔗
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-
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Subspace Detours Meet Gromov-Wasserstein
(
Spotlight
)
>
link
SlidesLive Video
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Clément Bonet · Nicolas Courty · François Septier · Lucas Drumetz
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-
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Measuring association with Wasserstein distances
(
Poster
)
>
link
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Johannes Wiesel
🔗
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-
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Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport
(
Poster
)
>
link
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Gonzalo Mena · Amin Nejatbakhsh · Erdem Varol · Jonathan Niles-Weed
🔗
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-
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Sinkhorn EM: An Expectation-Maximizationalgorithm based on entropic optimal transport
(
Spotlight
)
>
link
SlidesLive Video
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Gonzalo Mena · Amin Nejatbakhsh · Erdem Varol · Jonathan Niles-Weed
🔗
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-
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Factored couplings in multi-marginal optimal transport via difference of convex programming
(
Poster
)
>
link
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Quang Huy TRAN · Hicham Janati · Ievgen Redko · Rémi Flamary · Nicolas Courty
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-
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Factored couplings in multi-marginal optimal transport via difference of convex programming
(
Spotlight
)
>
link
SlidesLive Video
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Quang Huy TRAN · Hicham Janati · Ievgen Redko · Rémi Flamary · Nicolas Courty
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Learning Revenue-Maximizing Auctions With Differentiable Matching
(
Poster
)
>
link
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Michael Curry · Uro Lyi · Tom Goldstein · John P Dickerson
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-
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Learning Revenue-Maximizing Auctions With Differentiable Matching
(
Spotlight
)
>
link
SlidesLive Video
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Michael Curry · Uro Lyi · Tom Goldstein · John P Dickerson
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-
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Entropic estimation of optimal transport maps
(
Poster
)
>
link
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Aram-Alexandre Pooladian · Jonathan Niles-Weed
🔗
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-
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Entropic estimation of optimal transport maps
(
Oral
)
>
link
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Aram-Alexandre Pooladian · Jonathan Niles-Weed
🔗
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-
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A Central Limit Theorems for Multidimensional Wasserstein Distances
(
Poster
)
>
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Alberto Gonzalez Sanz · Loubes Jean-Michel · Eustasio Barrio
🔗
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-
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Variational Wasserstein gradient flow
(
Poster
)
>
link
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Jiaojiao Fan · Amirhossein Taghvaei · Yongxin Chen
🔗
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-
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Discrete Schrödinger Bridges with Applications to Two-Sample Homogeneity Testing
(
Poster
)
>
link
|
Zaid Harchaoui · Lang Liu · Soumik Pal
🔗
|
-
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Discrete Schrödinger Bridges with Applications to Two-Sample Homogeneity Testing
(
Oral
)
>
link
|
Zaid Harchaoui · Lang Liu · Soumik Pal
🔗
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-
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Towards an FFT for measures
(
Poster
)
>
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Paul Catala · Mathias Hockmann · Stefan Kunis · Markus Wageringel
🔗
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-
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On Combining Expert Demonstrations in Imitation Learning via Optimal Transport
(
Poster
)
>
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ilana sebag · Samuel Cohen · Marc Deisenroth
🔗
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-
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Sliced Multi-Marginal Optimal Transport
(
Poster
)
>
link
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Samuel Cohen · Alexander Terenin · Yannik Pitcan · Brandon Amos · Marc Deisenroth · Senanayak Sesh Kumar Karri
🔗
|
-
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Implicit Riemannian Concave Potential Maps
(
Poster
)
>
link
|
Danilo Jimenez Rezende · Sébastien Racanière
🔗
|
-
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Implicit Riemannian Concave Potential Maps
(
Oral
)
>
link
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Danilo Jimenez Rezende · Sébastien Racanière
🔗
|
-
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Multistage Monge Kantorovich Problem applied to optimal ecological transition
(
Poster
)
>
link
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Clara Lage · Emmanuel Gobet
🔗
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-
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Wasserstein Adversarially Regularized Graph Autoencoder
(
Poster
)
>
link
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Huidong Liang · Junbin Gao
🔗
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-
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Likelihood Training of Schrödinger Bridges using Forward-Backward SDEs Theory
(
Poster
)
>
link
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Tianrong Chen · Guan-Horng Liu · Evangelos Theodorou
🔗
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-
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Efficient estimates of optimal transport via low-dimensional embeddings
(
Poster
)
>
link
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Patric Fulop · Vincent Danos
🔗
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-
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Optimal Transport losses and Sinkhorn algorithm with general convex regularization
(
Poster
)
>
link
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Augusto Gerolin · Simone Di Marino
🔗
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-
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Towards interpretable contrastive word mover's embedding
(
Poster
)
>
link
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ruijie jiang · Julia Gouvea · Eric L Miller · David Hammer · Shuchin Aeron
🔗
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-
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Optimizing Functionals on the Space of Probabilities with Input Convex Neural Network
(
Poster
)
>
link
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David Alvarez-Melis · Yair Schiff · Youssef Mroueh
🔗
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-
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Optimizing Functionals on the Space of Probabilities with Input Convex Neural Network
(
Spotlight
)
>
link
SlidesLive Video
|
David Alvarez-Melis · Yair Schiff · Youssef Mroueh
🔗
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-
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Dual Regularized Optimal Transport
(
Poster
)
>
link
|
Rishi Sonthalia · Anna Gilbert
🔗
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