NeurIPS 2023 Workshop OTML Submissions

On Schrödinger Bridge Matching and Expectation Maximization
Rob Brekelmans, Kirill Neklyudov
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Fourier-Based Bounds for Wasserstein Distances and Their Implications in Computational Inversion
Wanli Hong, Vladimir A Kobzar, Kui Ren
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Outlier-Robust Wasserstein DRO
Sloan Nietert, Ziv Goldfeld, Soroosh Shafieezadeh-Abadeh
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Network Regression with Wasserstein Distances
Alexander Zalles, Kai M. Hung, Ann E. Finneran, Lydia Beaudrot, Cesar Uribe
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Adaptive Algorithms for Continuous-Time Transport: Homotopy-Driven Sampling and a New Interacting Particle System
Aimee Maurais, Youssef Marzouk
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Optimal Transport for Measures with Noisy Tree Metric
Tam Le, Truyen Nguyen, Kenji Fukumizu
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Applications of Optimal Transport Distances in Unsupervised AutoML
Prabhant Singh, Joaquin Vanschoren
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Unsupervised Learning Permutations for TSP using Gumbel-Sinkhorn Operator
Yimeng Min, Carla Gomes
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
A generative flow model for conditional sampling via optimal transport
Jason Alfonso, Ricardo Baptista, Anupam Bhakta, Noam Gal, Alfin Hou, Vasilisa Lyubimova, Daniel Pocklington, Josef Sajonz, Giulio Trigila, Ryan Tsai
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Estimating Fréchet bounds for validating programmatic weak supervision
Felipe Maia Polo, Mikhail Yurochkin, Moulinath Banerjee, Subha Maity, Yuekai Sun
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
A Computational Framework for Solving Wasserstein Lagrangian Flows
Kirill Neklyudov, Rob Brekelmans, Alexander Tong, Lazar Atanackovic, qiang liu, Alireza Makhzani
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Repairing Regressors for Fair Binary Classification at Any Decision Threshold
Kweku Kwegyir-Aggrey, Jessica Dai, A. Feder Cooper, John Dickerson, Keegan Hines, Suresh Venkatasubramanian
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Causal Discovery via Monotone Triangular Transport Maps
Sina Akbari, Luca Ganassali, Negar Kiyavash
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Optimal Transport with Adaptive Regularisation
Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Quantum Theory and Application of Contextual Optimal Transport
Nicola Mariella, Jannis Born, Albert Akhriev, Francesco Tacchino, Christa Zoufal, Eugene Koskin, Ivano Tavernelli, Stefan Woerner, Marianna Rapsomaniki, Sergiy Zhuk
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Learning via Wasserstein-Based High Probability Generalisation Bounds
Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Semidefinite Relaxations of the Gromov-Wasserstein Distance
Junyu Chen, Binh Nguyen, Yong Sheng Soh
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Fast and Accurate Cost-Scaling Algorithm for the Semi-Discrete Optimal Transport
Pankaj K Agarwal, Sharath Raghvendra, Pouyan Shirzadian, Keegan Yao
- Published: 27 Oct 2023, Last Modified: 17 Jan 2025
- OTML 2023 Poster
- Readers: Everyone
Optimal transport for vector Gaussian mixture models
Jiening Zhu, Kaiming Xu, Allen Tannenbaum
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Semi-discrete Gromov-Wasserstein distances: Existence of Gromov-Monge Maps and Statistical Theory
Gabriel Rioux, Ziv Goldfeld, Kengo Kato
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Entropic Gromov-Wasserstein Distances: Stability and Algorithms
Gabriel Rioux, Ziv Goldfeld, Kengo Kato
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Towards a Statistical Theory of Learning to Learn In-context with Transformers
Youssef Mroueh
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Oral
- Readers: Everyone
Normalizing flow neural networks by JKO scheme
Chen Xu, Xiuyuan Cheng, Yao Xie
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
Computing high-dimensional optimal transport by flow neural networks
Chen Xu, Xiuyuan Cheng, Yao Xie
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone
SpecTr++: Improved transport plans for speculative decoding of large language models
Kwangjun Ahn, Ahmad Beirami, Ziteng Sun, Ananda Theertha Suresh
- Published: 27 Oct 2023, Last Modified: 28 Dec 2023
- OTML 2023 Poster
- Readers: Everyone