Cover Image

Progressive Tempering Sampler with Diffusion

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rissanen, Severi, OuYang, RuiKang, He, Jiajun, Chen, Wenlin, Heinonen, Markus, Solin, Arno, Hernández-Lobato, José Miguel
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving Discrete Diffusion Models via Structured Preferential Generation
by: Rissanen, Severi, et al.
Published: (2024)

Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs
by: Rissanen, Severi, et al.
Published: (2024)

BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching
by: OuYang, RuiKang, et al.
Published: (2024)

A Diffusive Classification Loss for Learning Energy-based Generative Models
by: OuYang, RuiKang, et al.
Published: (2026)

Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
by: Laabid, Najwa, et al.
Published: (2024)

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers
by: He, Jiajun, et al.
Published: (2025)

Stochastic Interpolants in Hilbert Spaces
by: Yu, James Boran, et al.
Published: (2026)

Training Neural Samplers with Reverse Diffusive KL Divergence
by: He, Jiajun, et al.
Published: (2024)

PriorGuide: Test-Time Prior Adaptation for Simulation-Based Inference
by: Yang, Yang, et al.
Published: (2025)

Softly Constrained Denoisers for Diffusion Models Applied to Partial Differential Equations
by: Yeom-Song, Victor M., et al.
Published: (2025)

Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences
by: Yu, Hanlin, et al.
Published: (2026)

DiffRatio: Training One-Step Diffusion Models Without Teacher Supervision
by: Chen, Wenlin, et al.
Published: (2025)

Continuously Tempered Diffusion Samplers
by: Erives, Ezra, et al.
Published: (2025)

Learning to Approximate Particle Smoothing Trajectories via Diffusion Generative Models
by: Tamir, Ella, et al.
Published: (2024)

Variational Gaussian Process Diffusion Processes
by: Verma, Prakhar, et al.
Published: (2023)

Diffusive Gibbs Sampling
by: Chen, Wenlin, et al.
Published: (2024)

Leveraging Task Structures for Improved Identifiability in Neural Network Representations
by: Chen, Wenlin, et al.
Published: (2023)

Streamlining Prediction in Bayesian Deep Learning
by: Li, Rui, et al.
Published: (2024)

Accelerating Relative Entropy Coding with Space Partitioning
by: He, Jiajun, et al.
Published: (2024)

Getting Free Bits Back from Rotational Symmetries in LLMs
by: He, Jiajun, et al.
Published: (2024)

Physics-Informed Variational State-Space Gaussian Processes
by: Hamelijnck, Oliver, et al.
Published: (2024)

Approximate Bayesian Inference via Bitstring Representations
by: Sladek, Aleksanteri, et al.
Published: (2025)

Heterophily-informed Message Passing
by: Wang, Haishan, et al.
Published: (2025)

Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization
by: Shrestha, Jatan, et al.
Published: (2026)

Flatness Improves Backbone Generalisation in Few-shot Classification
by: Li, Rui, et al.
Published: (2024)

RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
by: He, Jiajun, et al.
Published: (2023)

RNE: plug-and-play diffusion inference-time control and energy-based training
by: He, Jiajun, et al.
Published: (2025)

DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick
by: Vali, Mohammad Hassan, et al.
Published: (2025)

Neural Flow Samplers with Shortcut Models
by: Chen, Wuhao, et al.
Published: (2025)

Diffusion Models as Cartoonists: The Curious Case of High Density Regions
by: Karczewski, Rafał, et al.
Published: (2024)

Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices
by: Viset, Frida, et al.
Published: (2024)

Non-separable Spatio-temporal Graph Kernels via SPDEs
by: Nikitin, Alexander, et al.
Published: (2021)

Compressing 3D Gaussian Splatting by Noise-Substituted Vector Quantization
by: Wang, Haishan, et al.
Published: (2025)

CREPE: Controlling Diffusion with Replica Exchange
by: He, Jiajun, et al.
Published: (2025)

Sources of Uncertainty in 3D Scene Reconstruction
by: Klasson, Marcus, et al.
Published: (2024)

Free energy Estimation on Any State Space
by: He, Jiajun, et al.
Published: (2026)

Efficient and Unbiased Sampling of Boltzmann Distributions via Consistency Models
by: Zhang, Fengzhe, et al.
Published: (2024)

Conditional Diffusion Sampling
by: Castro-Macías, Francisco M., et al.
Published: (2026)

Diffusion-PINN Sampler
by: Shi, Zhekun, et al.
Published: (2024)

The Spacetime of Diffusion Models: An Information Geometry Perspective
by: Karczewski, Rafał, et al.
Published: (2025)