Diffusion-PINN Sampler
Fuente:
arXiv
Saved in:
| Main Authors: | Shi, Zhekun, Yu, Longlin, Xie, Tianyu, Zhang, Cheng |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Kernel Semi-Implicit Variational Inference
by: Cheng, Ziheng, et al.
Published: (2024)
by: Cheng, Ziheng, et al.
Published: (2024)
Reflected Flow Matching
by: Xie, Tianyu, et al.
Published: (2024)
by: Xie, Tianyu, et al.
Published: (2024)
Functional Gradient Flows for Constrained Sampling
by: Zhang, Shiyue, et al.
Published: (2024)
by: Zhang, Shiyue, et al.
Published: (2024)
A Kernel Approach for Semi-implicit Variational Inference
by: Yu, Longlin, et al.
Published: (2026)
by: Yu, Longlin, et al.
Published: (2026)
Continuous Semi-Implicit Models
by: Yu, Longlin, et al.
Published: (2025)
by: Yu, Longlin, et al.
Published: (2025)
Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
by: Tang, Luhan, et al.
Published: (2026)
by: Tang, Luhan, et al.
Published: (2026)
Single-Step Consistent Diffusion Samplers
by: Jutras-Dubé, Pascal, et al.
Published: (2025)
by: Jutras-Dubé, Pascal, et al.
Published: (2025)
Progressive Tempering Sampler with Diffusion
by: Rissanen, Severi, et al.
Published: (2025)
by: Rissanen, Severi, et al.
Published: (2025)
Corrected Samplers for Discrete Flow Models
by: Wan, Zhengyan, et al.
Published: (2026)
by: Wan, Zhengyan, et al.
Published: (2026)
Particle Denoising Diffusion Sampler
by: Phillips, Angus, et al.
Published: (2024)
by: Phillips, Angus, et al.
Published: (2024)
Adaptive Destruction Processes for Diffusion Samplers
by: Gritsaev, Timofei, et al.
Published: (2025)
by: Gritsaev, Timofei, et al.
Published: (2025)
Importance Weighted Score Matching for Diffusion Samplers with Enhanced Mode Coverage
by: Wang, Chenguang, et al.
Published: (2025)
by: Wang, Chenguang, et al.
Published: (2025)
Training Neural Samplers with Reverse Diffusive KL Divergence
by: He, Jiajun, et al.
Published: (2024)
by: He, Jiajun, et al.
Published: (2024)
Proximal Diffusion Neural Sampler
by: Guo, Wei, et al.
Published: (2025)
by: Guo, Wei, et al.
Published: (2025)
Continuously Tempered Diffusion Samplers
by: Erives, Ezra, et al.
Published: (2025)
by: Erives, Ezra, et al.
Published: (2025)
Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
by: Cheng, Ziheng, et al.
Published: (2025)
by: Cheng, Ziheng, et al.
Published: (2025)
The Diffusion Duality, Chapter II: $Ψ$-Samplers
by: Deschenaux, Justin, et al.
Published: (2026)
by: Deschenaux, Justin, et al.
Published: (2026)
Learnable Sampler Distillation for Discrete Diffusion Models
by: Fu, Feiyang, et al.
Published: (2025)
by: Fu, Feiyang, et al.
Published: (2025)
One-Step Diffusion Samplers via Self-Distillation and Deterministic Flow
by: Jutras-Dube, Pascal, et al.
Published: (2025)
by: Jutras-Dube, Pascal, et al.
Published: (2025)
Rethinking Losses for Diffusion Bridge Samplers
by: Sanokowski, Sebastian, et al.
Published: (2025)
by: Sanokowski, Sebastian, et al.
Published: (2025)
On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models
by: Zhang, Yi, et al.
Published: (2025)
by: Zhang, Yi, et al.
Published: (2025)
Load--Reserve Wasserstein Propagation for Isotropic Diffusion Samplers
by: Lyu, Zicheng, et al.
Published: (2026)
by: Lyu, Zicheng, et al.
Published: (2026)
Multi-Environment GLAMP: Approximate Message Passing for Transfer Learning with Applications to Lasso-based Estimators
by: Wang, Longlin, et al.
Published: (2025)
by: Wang, Longlin, et al.
Published: (2025)
B-PL-PINN: Stabilizing PINN Training with Bayesian Pseudo Labeling
by: Innerebner, Kevin, et al.
Published: (2025)
by: Innerebner, Kevin, et al.
Published: (2025)
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints
by: Kong, Lingkai, et al.
Published: (2024)
by: Kong, Lingkai, et al.
Published: (2024)
Attention-Based Sampler for Diffusion Language Models
by: Zhou, Yuyan, et al.
Published: (2026)
by: Zhou, Yuyan, et al.
Published: (2026)
Diffusion Path Samplers via Sequential Monte Carlo
by: Young, James Matthew, et al.
Published: (2026)
by: Young, James Matthew, et al.
Published: (2026)
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers
by: Liang, Yuchen, et al.
Published: (2024)
by: Liang, Yuchen, et al.
Published: (2024)
Diffusion Language Models are Provably Optimal Parallel Samplers
by: Jiang, Haozhe, et al.
Published: (2025)
by: Jiang, Haozhe, et al.
Published: (2025)
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
by: Zhang, Dinghuai, et al.
Published: (2023)
by: Zhang, Dinghuai, et al.
Published: (2023)
Rethinking Timesteps Samplers and Prediction Types
by: Xie, Bin, et al.
Published: (2025)
by: Xie, Bin, et al.
Published: (2025)
Transition Path Sampling with Improved Off-Policy Training of Diffusion Path Samplers
by: Seong, Kiyoung, et al.
Published: (2024)
by: Seong, Kiyoung, et al.
Published: (2024)
Value Gradient Sampler: Learning Invariant Value Functions for Equivariant Diffusion Sampling
by: Hwang, Himchan, et al.
Published: (2025)
by: Hwang, Himchan, et al.
Published: (2025)
Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees
by: Liang, Yuchen, et al.
Published: (2025)
by: Liang, Yuchen, et al.
Published: (2025)
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler
by: Blessing, Denis, et al.
Published: (2025)
by: Blessing, Denis, et al.
Published: (2025)
DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models
by: Zhou, Xueyu, et al.
Published: (2026)
by: Zhou, Xueyu, et al.
Published: (2026)
Swift Sampler: Efficient Learning of Sampler by 10 Parameters
by: Yao, Jiawei, et al.
Published: (2024)
by: Yao, Jiawei, et al.
Published: (2024)
The Crucial Role of Samplers in Online Direct Preference Optimization
by: Shi, Ruizhe, et al.
Published: (2024)
by: Shi, Ruizhe, et al.
Published: (2024)
Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching
by: Blessing, Denis, et al.
Published: (2026)
by: Blessing, Denis, et al.
Published: (2026)
Convergence of Deterministic and Stochastic Diffusion-Model Samplers: A Simple Analysis in Wasserstein Distance
by: Beyler, Eliot, et al.
Published: (2025)
by: Beyler, Eliot, et al.
Published: (2025)
Similar Items
-
Kernel Semi-Implicit Variational Inference
by: Cheng, Ziheng, et al.
Published: (2024) -
Reflected Flow Matching
by: Xie, Tianyu, et al.
Published: (2024) -
Functional Gradient Flows for Constrained Sampling
by: Zhang, Shiyue, et al.
Published: (2024) -
A Kernel Approach for Semi-implicit Variational Inference
by: Yu, Longlin, et al.
Published: (2026) -
Continuous Semi-Implicit Models
by: Yu, Longlin, et al.
Published: (2025)