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Workshop Sun, Dec 7, 2025 • 8:00 AM – 5:00 PM PST Upper Level Room 7

Frontiers in Probabilistic Inference: Learning meets Sampling

Tara Akhound-Sadegh · Michael Albergo · Joey Bose · Marylou Gabrié · Louis Grenioux · Guan-Horng Liu · Kirill Neklyudov · Grant Rotskoff · Eva Smorodina · Alexander Tong
Project Page [ OpenReview] 

Video

Chat is not available.

Schedule

Timezone: America/Los_Angeles
9:20 AM
Coffee break
11:15 AM
Poster Session I
12:15 PM
Lunch
3:25 PM
Coffee break
Discrete Stochastic Localization for Non-Autoregressive Generation
Yunshu Wu · Jiayi Cheng · Rob Brekelmans · Vagelis Papalexakis · Greg Ver Steeg
Control Consistency Losses for Diffusion Bridges
Samuel Howard · Nikolas Nüsken · Jakiw Pidstrigach
Control Consistency Losses for Diffusion Bridges
Samuel Howard · Nikolas Nüsken · Jakiw Pidstrigach
Tokenised Flow Matching for Hierarchical Simulation Based Inference
Giovanni Charles · Seth Flaxman · Elizaveta Semenova · Oliver Watson
Learning Paths for Dynamic Transport: A Control Perspective
Aimee Maurais · Bamdad Hosseini · Youssef Marzouk
STARS: Segment-level Token Alignment via Rejection Sampling in Large Language Models
Mohammad Atif Quamar · Mohammad Areeb · Mikhail Kuznetsov · Muslum Ozmen · Z. Berkay Celik
Inference-time alignment of language models by importance sampling on pre-logit space
Sekitoshi Kanai · Kazumune Hashimoto · Tsukasa Yoshida
Model Agnostic Conditioning of Boltzmann Generators for Peptide Cyclization
Benjamin du Pont · Alex Abrudan · Rob Scrutton · Vladimir Radenkovic · Haowen Zhao · Tuomas Knowles
Model Agnostic Conditioning of Boltzmann Generators for Peptide Cyclization
Benjamin du Pont · Alex Abrudan · Rob Scrutton · Vladimir Radenkovic · Haowen Zhao · Tuomas Knowles
Compression Meets Sampling: On Energy-Efficient Random Variate Generation
Johann Ukrow · Anna Kazachkova · Nicolas Alder · Sven Köhler · Ralf Herbrich
torchgfn: A PyTorch GFlowNet library
Joseph Viviano · Omar G. Younis · Sanghyeok Choi · Victor Schmidt · Yoshua Bengio · Salem Lahlou
Weighted Conditional Flow Matching
Sergio Calvo Ordoñez · Matthieu Meunier · Alvaro Cartea · Christoph Reisinger · Yarin Gal · José Miguel Hernández-Lobato
Learning Discrete Distributions from Metastable Data via Pseudo-Likelihood
Abhijith Jayakumar · Andrey Lokhov · Sidhant Misra · Marc Vuffray
Ordered Diversity Sampling for Text
Ashish Tiwari · Mukul Singh · Ananya Singha · Arjun Radhakrishna
GNN-Guided Block Selection in Gibbs MCMC
Benjamin Dayan · Bhaskar Mishra · Justin Svegliato · Stuart J Russell
Uncertainty Weighted Deep Ensemble to Enhance Protein Property Prediction
Alif Bin Abdul Qayyum · Amir Hossein Rahmati · Xiaoning Qian · Byung-Jun Yoon
Value Matching: Scalable and Gradient-Free Reward-Guided Flow Adaptation
Cristian Jensen · Luca Schaufelberger · Riccardo De Santi · Kjell Jorner · Andreas Krause
e-SimFT: Pareto-Optimal Sampling of Generative Design Models Fine-tuned with Simulation Feedback
Hyunmin Cheong · Mohammadmehdi Ataei · Amir Khasahmadi · Pradeep Kumar Jayaraman
Multimarginal Flow Matching with Adversarially Learnt Interpolants
Oskar Kviman · Kirill Tamogashev · Nicola Branchini · Víctor Elvira · Jens Lagergren · Nikolay Malkin
GAP: Guided Diffusion for A Priori Transition State Sampling
Hyukjun Lim · Soojung Yang · Lucas Pinede · Miguel Steiner · Yuanqi Du · Rafael Gomez-Bombarelli
Data Generation without Function Estimation
Hadi Daneshmand · Ashkan Soleymani
Categorical Flow Matching via Simplex-to-Euclidean Bijections
Bernardo Williams · Victor Yeom-Song · Arto Klami
An Eulerian Perspective on Straight-Line Sampling
Panagiotis Tsimpos · Youssef Marzouk
Counterdiabatic Hamiltonian Monte Carlo
Reuben Cohn-Gordon · Uros Seljak · Dries Sels
Combined Representation and Generation with Diffusive State Prediction Information Bottleneck
Richard John · Yunrui Qiu · Lukas Herron · Pratyush Tiwary
Relative Trajectory Balance is equivalent to Trust-PCL
Tristan Deleu · Padideh Nouri · Yoshua Bengio · Doina Precup
Data-to-Energy Stochastic Dynamics
Kirill Tamogashev · Nikolay Malkin
A Unification of Discrete, Gaussian, and Simplicial Diffusion
Nuria Chandra · Alan Amin · Andrew Wilson
Sampling from Energy distributions with Target Concrete Score Identity
Sergei Kholkin · Francisco Vargas · Aleksandr Korotin
Robust Multi-task Modeling for Bayesian Optimization via In-Context Learning
Yucen Li · Samuel Daulton · Samuel Müller · Andrew Wilson · Eytan Bakshy
Sampling Strategies for Transformer-Based Mechanism Synthesis
Mohammadmehdi Ataei · Diana Bolanos · Pradeep Kumar Jayaraman
Pokie: Posterior Accuracy and Model Comparison
Sammy Sharief · Justine Zeghal · Gabriel Missael Barco · Pablo Lemos · Yashar Hezaveh · Laurence Perreault-Levasseur
Convergences guarantees of GFlowNets
Tristan Deleu · Yoshua Bengio
Variational Entropy Search is Just 1D Regression
Michael Pearce · Thomas Pollak · Luke Hudlass-Galley
Steering Pretrained Drafters during Speculative Decoding
Frédéric Berdoz · Peer Rheinboldt · Roger Wattenhofer
Machine-Learned Sampling of Conditioned Path Measures
Qijia Jiang · Reuben Cohn-Gordon
Generalized Constrained Flow Matching for Constraint-Aware Generative Modeling
JINHAO LIANG · Sandeep Madireddy · Ferdinando Fioretto
Towards Integrating Uncertainty for Domain-Agnostic Segmentation
Jesse Brouwers · Xiaoyan Xing · Alexander Timans
Token-Level Guided Discrete Diffusion for Membrane Protein Design
Shrey Goel · Peregrine Schray · Yinuo Zhang · Sophia Vincoff · Huong Kratochvil · Pranam Chatterjee
DDS-E-Sim: A Transformer-based Probabilistic Generative Framework for Simulating Error-Prone DNA Sequences for DNA Data Storage
Mst. Naznin · Swarup Sidhartho Mondol · Adnan Faruq · Debashmita Saha · Ahmed Rumi · A. B. M. Alim Al Islam
A Sampling-Based Domain Generalization Study with Diffusion Generative Models
Ye Zhu · Yu Wu · Duo Xu · Zhiwei Deng · Yan Yan · Olga Russakovsky
Can We Estimate The Entropy Of Arbitrary Distributions Known Up To A Normalization Constant?
Safa Messaoud · Skander Charni · Elaa Bouazza · Ali Pourghasemi Fatideh · Halima Bensmail
Learning Boltzmann Generators via Constrained Mass Transport
Christopher von Klitzing · Denis Blessing · Henrik Schopmans · Pascal Friederich · Gerhard Neumann
moPPIt-v3: Motif-Specific Peptides Generated via Multi-Objective-Guided Discrete Flow Matching
Tong Chen · Zachary Quinn · Yinuo Zhang · Pranam Chatterjee
Constrained Molecular Generation via Sequential Flow Model Fine-Tuning
Sven Gutjahr · Riccardo De Santi · Luca Schaufelberger · Kjell Jorner · Andreas Krause
Constrained Molecular Generation via Sequential Flow Model Fine-Tuning
Sven Gutjahr · Riccardo De Santi · Luca Schaufelberger · Kjell Jorner · Andreas Krause
Enhancing Diversity in Large Language Models via Determinantal Point Processes
Yilei Chen · Lorenz Wolf · Souradip Chakraborty · Aldo Pacchiano · Yannis Paschalidis
Adaptive Destruction Processes for Diffusion Samplers
Timofei Gritsaev · Nikita Morozov · Kirill Tamogashev · Daniil Tiapkin · Sergey Samsonov · Alexey Naumov · Dmitry Vetrov · Nikolay Malkin
Adaptive Destruction Processes for Diffusion Samplers
Timofei Gritsaev · Nikita Morozov · Kirill Tamogashev · Daniil Tiapkin · Sergey Samsonov · Alexey Naumov · Dmitry Vetrov · Nikolay Malkin
Entangled Schrödinger Bridge Matching
Sophia Tang · Yinuo Zhang · Pranam Chatterjee