Characteristic Learning for Provable One Step Generation
Zhao Ding, Chenguang Duan, Yuling Jiao, Ruoxuan Li, Jerry Zhijian Yang, Pingwen Zhang
cs.LG, cs.AI, cs.NA, math.NA, math.ST, stat.TH
Submitted: 2026-08-09
Updated: 2026-08-11
Code: https://github.com/burning489/CharacteristicGenerator
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
- Stochastic interpolants with data-dependent couplings
- Convergence of Deterministic and Stochastic Diffusion-Model Samplers: A Simple Analysis in Wasserstein Distance
- Deep conditional distribution learning via conditional F\"ollmer flow
- Distribution Approximation and Statistical Estimation Guarantees of Generative Adversarial Networks
- Semi-Supervised Deep Sobolev Regression: Estimation and Variable Selection by ReQU Neural Network
- Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
- Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
- Convergence of Continuous Normalizing Flows for Learning Probability Distributions
- Convergence Analysis of Flow Matching in Latent Space with Transformers
- Towards a mathematical theory for consistency training in diffusion models
- Rectified Flow: A Marginal Preserving Approach to Optimal Transport
- Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
- DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models
- Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
- Hierarchical Text-Conditional Image Generation with CLIP Latents
- Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
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