One-Step Generative Modeling via Unbalanced Optimal Transport

arXiv:2609.32708 · cs.IT, cs.LG, math.IT · Submitted 2026-09-26 · Read on arXiv

cs.IT, cs.LG, math.IT

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Gradient Flow — 25× in this paper · explained in 2 episodes
• Optimal Transport — 25× in this paper · explained in 5 episodes
• Generative Modeling — 18× in this paper · explained in 3 episodes
• Generative Model — 12× in this paper · explained in 2 episodes
• Generative Models — 11× in this paper · explained in 2 episodes
• Regularization — 8× in this paper · explained in 3 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Transformer — 7× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 6× in this paper
• Latent Space — 6× in this paper · explained in 7 episodes
• Wasserstein Distance — 4× in this paper · explained in 4 episodes
• 2-Wasserstein Distance — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Diffusion Models — 3× in this paper · explained in 6 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Domain Adaptation — 2× in this paper · explained in 5 episodes
• Flow Matching — 2× in this paper · explained in 8 episodes
• Initial Data — 2× in this paper · explained in 2 episodes
• Latent Diffusion Model — 2× in this paper · explained in 2 episodes
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Sample Complexity — 2× in this paper · explained in 15 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Distribution Matching — 1× in this paper · explained in 2 episodes
• Entanglement — 1× in this paper · explained in 4 episodes
• Frechet Inception Distance — 1× in this paper
• Latent Representation — 1× in this paper · explained in 2 episodes
• Machine Unlearning — 1× in this paper · explained in 2 episodes
• Mean-Field Dynamics — 1× in this paper · explained in 2 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Rectified Flow — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes

Sources

• Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models
• Gradient Flow Drifting: Generative Modeling via Wasserstein Gradient Flows of KDE-Approximated Divergences
• Unlearning for One-Step Generative Models via Unbalanced Optimal Transport
• Generative Modeling via Drifting
• Learning Monge maps with constrained drifting models
• Kernel-Gradient Drifting Models
• Representation Distribution Matching for One-Step Visual Generation
• Drifting Fields are not Conservative
• On the Wasserstein Gradient Flow Interpretation of Drifting Models
• One-Step Generative Modeling via Wasserstein Gradient Flows
• Sinkhorn-Drifting Generative Models
• Generative Drifting for Conditional Medical Image Generation
• Is There an Analog of Nesterov Acceleration for MCMC?
• Unbalanced Diffusion Schr\"odinger Bridge
• Sinkhorn Divergences for Unbalanced Optimal Transport
• Speech Enhancement Based on Drifting Models
• Lookahead Drifting Model
• Distilling Drifting Transformers with Representation Autoencoders
• Positive-Only Drifting Policy Optimization

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