Copertina

A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Tarasov, Roman, Mokrov, Petr, Gazdieva, Milena, Burnaev, Evgeny, Korotin, Alexander
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
di: Gazdieva, Milena, et al.
Pubblicazione: (2024)

Estimating Barycenters of Distributions with Neural Optimal Transport
di: Kolesov, Alexander, et al.
Pubblicazione: (2024)

An Optimal Transport Perspective on Unpaired Image Super-Resolution
di: Gazdieva, Milena, et al.
Pubblicazione: (2022)

Light Unbalanced Optimal Transport
di: Gazdieva, Milena, et al.
Pubblicazione: (2023)

Energy-guided Entropic Neural Optimal Transport
di: Mokrov, Petr, et al.
Pubblicazione: (2023)

Neural Optimal Transport with General Cost Functionals
di: Asadulaev, Arip, et al.
Pubblicazione: (2022)

Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme
di: Persiianov, Mikhail, et al.
Pubblicazione: (2025)

Variational Entropic Optimal Transport
di: Dyachenko, Roman, et al.
Pubblicazione: (2026)

Energy-Guided Continuous Entropic Barycenter Estimation for General Costs
di: Kolesov, Alexander, et al.
Pubblicazione: (2023)

Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization
di: Persiianov, Mikhail, et al.
Pubblicazione: (2024)

Uncovering Challenges of Solving the Continuous Gromov-Wasserstein Problem
di: Carrasco, Xavier Aramayo, et al.
Pubblicazione: (2023)

Optimal Flow Matching: Learning Straight Trajectories in Just One Step
di: Kornilov, Nikita, et al.
Pubblicazione: (2024)

Rethinking Optimal Transport in Offline Reinforcement Learning
di: Asadulaev, Arip, et al.
Pubblicazione: (2024)

Loss Barcode: A Topological Measure of Escapability in Loss Landscapes
di: Barannikov, Serguei, et al.
Pubblicazione: (2020)

Light and Optimal Schrödinger Bridge Matching
di: Gushchin, Nikita, et al.
Pubblicazione: (2024)

Light Schrödinger Bridge
di: Korotin, Alexander, et al.
Pubblicazione: (2023)

Adversarial Schrödinger Bridge Matching
di: Gushchin, Nikita, et al.
Pubblicazione: (2024)

Online Algorithm for Aggregating Experts' Predictions with Unbounded Quadratic Loss
di: Korotin, Alexander, et al.
Pubblicazione: (2025)

Mixability of Integral Losses: a Key to Efficient Online Aggregation of Functional and Probabilistic Forecasts
di: Korotin, Alexander, et al.
Pubblicazione: (2019)

Optimal Transport Maps are Good Voice Converters
di: Asadulaev, Arip, et al.
Pubblicazione: (2024)

Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives
di: Balakrishnan, Sivaraman, et al.
Pubblicazione: (2025)

EBES: Easy Benchmarking for Event Sequences
di: Osin, Dmitry, et al.
Pubblicazione: (2024)

Risk-Averse Reinforcement Learning with Itakura-Saito Loss
di: Udovichenko, Igor, et al.
Pubblicazione: (2025)

RTD-Lite: Scalable Topological Analysis for Comparing Weighted Graphs in Learning Tasks
di: Tulchinskii, Eduard, et al.
Pubblicazione: (2025)

Displacement-Sparse Neural Optimal Transport
di: Chen, Peter, et al.
Pubblicazione: (2025)

SeqNAS: Neural Architecture Search for Event Sequence Classification
di: Udovichenko, Igor, et al.
Pubblicazione: (2024)

Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
di: Mukherjee, Kunal, et al.
Pubblicazione: (2026)

MLEM: Generative and Contrastive Learning as Distinct Modalities for Event Sequences
di: Moskvoretskii, Viktor, et al.
Pubblicazione: (2024)

Disentanglement Learning via Topology
di: Balabin, Nikita, et al.
Pubblicazione: (2023)

SOTAlign: Semi-Supervised Alignment of Unimodal Vision and Language Models via Optimal Transport
di: Roschmann, Simon, et al.
Pubblicazione: (2026)

On the Equivalence of Optimal Transport Problem and Action Matching with Optimal Vector Fields
di: Kornilov, Nikita, et al.
Pubblicazione: (2025)

Generative Conditional Distributions by Neural (Entropic) Optimal Transport
di: Nguyen, Bao, et al.
Pubblicazione: (2024)

InfoBridge: Mutual Information estimation via Bridge Matching
di: Kholkin, Sergei, et al.
Pubblicazione: (2025)

cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
di: Qiu, Yixuan
Pubblicazione: (2026)

GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs
di: Zhelnin, Maxim, et al.
Pubblicazione: (2024)

Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning
di: Cheng, Ziheng, et al.
Pubblicazione: (2026)

Learning Under Laws: A Constraint-Projected Neural PDE Solver that Eliminates Hallucinations
di: Singha, Mainak
Pubblicazione: (2025)

Is Optimal Transport Necessary for Inverse Reinforcement Learning?
di: Dong, Zixuan, et al.
Pubblicazione: (2025)

When and Why Adversarial Training Improves PINNs: A Neural Tangent Kernel Perspective
di: Cao, Yuan-dong, et al.
Pubblicazione: (2026)

Regret-Based Defense in Adversarial Reinforcement Learning
di: Belaire, Roman, et al.
Pubblicazione: (2023)