:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Havens, Aaron, Karrer, Brian, Shaul, Neta
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2605.03984
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective
por: Shaul, Neta, et al.
Publicado: (2024)

GLASS Flows: Transition Sampling for Alignment of Flow and Diffusion Models
por: Holderrieth, Peter, et al.
Publicado: (2025)

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
por: Havens, Aaron, et al.
Publicado: (2025)

Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
por: Shaul, Neta, et al.
Publicado: (2024)

Generator Matching: Generative modeling with arbitrary Markov processes
por: Holderrieth, Peter, et al.
Publicado: (2024)

Transition Matching: Scalable and Flexible Generative Modeling
por: Shaul, Neta, et al.
Publicado: (2025)

Edit Flows: Flow Matching with Edit Operations
por: Havasi, Marton, et al.
Publicado: (2025)

Discrete Flow Matching
por: Gat, Itai, et al.
Publicado: (2024)

Training-free Linear Image Inverses via Flows
por: Pokle, Ashwini, et al.
Publicado: (2023)

Corrector Sampling in Language Models
por: Gat, Itai, et al.
Publicado: (2025)

Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators
por: Roy, Samrendra, et al.
Publicado: (2026)

Learning Hidden Markov Models Using Conditional Samples
por: Kakade, Sham M., et al.
Publicado: (2023)

Asymptotically Optimal Change Detection for Unnormalized Pre- and Post-Change Distributions
por: Adibi, Arman, et al.
Publicado: (2024)

Non-Linear Reinforcement Learning in Large Action Spaces: Structural Conditions and Sample-efficiency of Posterior Sampling
por: Agarwal, Alekh, et al.
Publicado: (2022)

Conditional Factuality Controlled LLMs with Generalization Certificates via Conformal Sampling
por: Ye, Kai, et al.
Publicado: (2026)

Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning
por: Namkoong, Hongseok, et al.
Publicado: (2020)

SCORENF: Score-based Normalizing Flows for Sampling Unnormalized distributions
por: Kanaujia, Vikas, et al.
Publicado: (2025)

GCHR : Goal-Conditioned Hindsight Regularization for Sample-Efficient Reinforcement Learning
por: Lei, Xing, et al.
Publicado: (2025)

Amortized Sampling with Transferable Normalizing Flows
por: Tan, Charlie B., et al.
Publicado: (2025)

Concept Layers: Enhancing Interpretability and Intervenability via LLM Conceptualization
por: Bidusa, Or Raphael, et al.
Publicado: (2025)

Sharpen Your Flow: Sharpness-Aware Sampling for Flow Matching
por: Gupta, Aditi, et al.
Publicado: (2026)

Generative Modeling with Continuous Flows: Sample Complexity of Flow Matching
por: Gaur, Mudit, et al.
Publicado: (2025)

Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
por: Akhound-Sadegh, Tara, et al.
Publicado: (2025)

A Sample Efficient Conditional Independence Test in the Presence of Discretization
por: Sun, Boyang, et al.
Publicado: (2025)

Learning Submodular Sequencing from Samples
por: Yuan, Jing, et al.
Publicado: (2024)

ProFlow: Zero-Shot Physics-Consistent Sampling via Proximal Flow Guidance
por: Yu, Zichao, et al.
Publicado: (2026)

Speculative Sampling with Reinforcement Learning
por: Wang, Chenan, et al.
Publicado: (2026)

FlowState: Sampling Rate Invariant Time Series Forecasting
por: Graf, Lars, et al.
Publicado: (2025)

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling, and Beyond
por: Nguyen-Tang, Thanh, et al.
Publicado: (2024)

More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling
por: Ishfaq, Haque, et al.
Publicado: (2024)

Flow Matching Guide and Code
por: Lipman, Yaron, et al.
Publicado: (2024)

Fast Sampling for Flows and Diffusions with Lazy and Point Mass Stochastic Interpolants
por: Damsholt, Gabriel, et al.
Publicado: (2026)

Order-Optimal Sample Complexity of Rectified Flows
por: Sahoo, Hari Krishna, et al.
Publicado: (2026)

Sample-efficient Adversarial Imitation Learning
por: Jung, Dahuin, et al.
Publicado: (2023)

FLOPS: Forward Learning with OPtimal Sampling
por: Ren, Tao, et al.
Publicado: (2024)

Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
por: Rahman, Md Musfiqur, et al.
Publicado: (2024)

Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling
por: Xu, Jian, et al.
Publicado: (2024)

Airfoil Diffusion: Denoising Diffusion Model For Conditional Airfoil Generation
por: Graves, Reid, et al.
Publicado: (2024)

Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance
por: McClellan, Joshua, et al.
Publicado: (2024)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
por: Liu, Zongkai, et al.
Publicado: (2024)