Towards Universal Wasserstein Barycenters through Flow Matching
cs.LG, cs.AI, stat.ML
Submitted: 2026-09-29
Updated: 2026-09-29
Terminology
Sources
- Density estimation using Real NVP
- Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks
- Learning with minibatch Wasserstein : asymptotic and gradient properties
- Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
- In Search of Lost Domain Generalization
- Classifier-Free Diffusion Guidance
- Adam: A Method for Stochastic Optimization
- Auto-Encoding Variational Bayes
- Estimating Barycenters of Distributions with Neural Optimal Transport
- Neural Optimal Transport
- Flow Matching for Generative Modeling
- Decoupled Weight Decay Regularization
- Multi-Source Domain Adaptation through Dataset Dictionary Learning in Wasserstein Space
- Entropic estimation of optimal transport maps
- Improving and generalizing flow-based generative models with minibatch optimal transport
- Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows
- mixup: Beyond Empirical Risk Minimization
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