probability flow

Sampling-Aware Quantization for Diffusion Models CVPR 2026 Stochastic Interpolants: A Unifying Framework for Flows and Diffusions JMLR 2025 When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets ICML 2025 Consistency Models for Scalable and Fast Simulation-Based Inference NeurIPS 2024 Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion ICLR 2024 DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow ICLR 2024 Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution AAAI 2024 Exploring the Optimal Choice for Generative Processes in Diffusion Models: Ordinary vs Stochastic Differential Equations NeurIPS 2023 Formulating Discrete Probability Flow Through Optimal Transport NeurIPS 2023 Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers ICML 2023 Self-Consistent Velocity Matching of Probability Flows NeurIPS 2023 Understanding DDPM Latent Codes Through Optimal Transport ICLR 2023 Regularized Autoencoders via Relaxed Injective Probability Flow AISTATS 2020