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Workshop Fri, Dec 11, 2026 • 8:00 AM – 5:00 PM AEDT MR C3.2

AI for Stochastic Dynamics: From Theoretical Foundations to Scientific Applications

Dai Shi ⋅ Andi Han ⋅ Bingxin Zhou ⋅ Luke Thompson ⋅ Valentin De Bortoli ⋅ Junbin Gao ⋅ José Miguel Hernández-Lobato
[ OpenReview] 

Abstract

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Schedule

Time zone: Conference local time zone
Zero-Flow Two-Sample Tests
Yakun Wang ⋅ Leyang Wang ⋅ Song Liu ⋅ Taiji Suzuki
SupportCal: Label-Free Calibration of Post-Trained LLMs via Reference Support and Corroboration
LINHAN LUO ⋅ Lequan Lin ⋅ Dai Shi ⋅ Feng Chen ⋅ José Miguel Hernández-Lobato ⋅ Junbin Gao
Structured Neural SDEs for Functional Calibration
Francesco Piatti ⋅ Andrea Iannucci ⋅ Thomas Cass
Generative Modeling With Learnable Noise Memory
Gabriel Nobis ⋅ Tim Korjakow ⋅ Luca Schmidt ⋅ Maximilian Springenberg ⋅ Thomas Demeester ⋅ Wojciech Samek ⋅ Manfred Opper ⋅ Tolga Birdal ⋅ Rembert Daems
Recovering Competing Reaction Channels in Doob’s Lagrangian Transition Path Sampling
Alessandro Licciardi ⋅ Ethan Eig ⋅ Andrew R Mitchell ⋅ Grant Rotskoff
Measuring Effective Data Resolution in Guided Diffusion Posteriors
Ridham Patel ⋅ Defu Cao ⋅ Jiacheng Pang ⋅ Yan Liu
Soft Metropolis-Hastings Correction for Molecular Generative Model Sampling
Hanqi Feng ⋅ Peng Qiu ⋅ Yujue Wang ⋅ Mengchun Zhang ⋅ Yu Liu ⋅ Qiaochu Xing ⋅ You Fan ⋅ Yiran Tao ⋅ Xianyang Chen ⋅ Barnabas Poczos
A Continuous-Discrete Switching Dynamical Model for Multi-Agent Interactions
Anushri Arora ⋅ Ralph E. Peterson ⋅ Dmitry Batenkov ⋅ Emily Mackevicius ⋅ Daniel Waxman ⋅ Matthew Levine
Fixed-Point Rates for Self-Distillation of Flow Maps
Stanic Tom ⋅ Quentin Bertrand ⋅ Joey Bose ⋅ Gauthier Gidel
Statistical Analysis of Inverse Entropy-Regularized Reinforcement Learning
Artemy Rubtsov ⋅ Denis Belomestny ⋅ Alexey Naumov ⋅ Sergey Samsonov
Numerical Integration on Bounded Domains via Learned Reflected Diffusions
Kirill Korolev ⋅ Artur Goldman ⋅ Timofei Gritsaev ⋅ Tigran Ramazyan ⋅ Nikita Morozov
Retention You Can Predict, Scope and Delete:\\ a $(\mu,\gamma,T)$ Law and a Structural Deletion Guarantee\\ for a Physics-Structured Memory Store
Pratik Jawahar ⋅ Riccardo Maggioni ⋅ Jonas Petersen ⋅ Matteo Cozzi ⋅ Gian-Alessandro Lombardi ⋅ Marek Gajewski ⋅ Camilla Mazzoleni ⋅ Federico Martelli ⋅ Maurizio Pierini
A Response Theory probe for learned stochastic AI simulators, tested on Lorenz-63
João P de Souza Böger ⋅ Francisco Pereira ⋅ Simon Driscoll ⋅ Niccolo Zagli ⋅ Valerio Lucarini
Controlled Koopman Machine for Interpretable Longitudinal Personalized Alzheimer's Disease Forecasting
Georgi Hrusanov ⋅ Duy-Cat Can ⋅ Duy-Thanh VU ⋅ Ivan Stoyanov ⋅ Sophie Tascedda ⋅ Margaret Ryan ⋅ Julien Bodelet ⋅ Katarzyna A Koscielska ⋅ Giovanni d'Ario ⋅ Carsten Magnus ⋅ Oliver Y Chén
Localizing Conditional Transport in Triangular Flows
Alex Johnson-Vázquez ⋅ Bamdad Hosseini
Predicting Bioluminescent Algal Blooms by Conditioning Neural Forecasts on Reconstructed Dynamics
Athulith Paraselli ⋅ Ciro Zhang ⋅ Melissa L Carter ⋅ George Sugihara
Are Seismic Foundation Models More Than Glorified Feature Extractors?
Laura Laurenti ⋅ David Liu ⋅ Brian Kulis ⋅ Men-Andrin Meier ⋅ Christopher Johnson
PDEFlow: Autonomous Agentic PDE Pipelines for Neural Operator Learning and Solver-Free Inference
Akshat Jani ⋅ Prathamesh Gadekar ⋅ Sagar Srinivas Sakhinana ⋅ Venkataramana Runkana
Efficient Active Learning for Continuous-Time Experiments
Samo Hromadka ⋅ Max Mowbray ⋅ Hrvoje Stojic ⋅ Victor Picheny
Multi-Fidelity Neural Operator Thompson Sampling
Rafael Oliveira ⋅ Neil Dhir
Normalizing Flow Maps
Francesco Maria Ruscio ⋅ Timothy James Hitge ⋅ Fred Peng ⋅ Danyal Rehman ⋅ Zander Blasingame ⋅ Michael Bronstein ⋅ Nicholas Boffi ⋅ Alexander Tong ⋅ Joey Bose
On the Stability and Convergence of Flow Map Training
Ishan Nath ⋅ Mathurin Massias ⋅ Joey Bose ⋅ Gauthier Gidel ⋅ Quentin Bertrand
Diffusion Distillation for Efficient Weather Ensembles
Yiming Yang ⋅ Valentin Brekke ⋅ James Briant ⋅ Serge Guillas
COMPOSE: Molecular Generation and Optimization with a Reusable Stochastic Rewrite Process
Rohin Maganti ⋅ Rahul Maganti ⋅ Mohamad-Gabriel Alameh ⋅ Pranam Chatterjee
Marchuk: A Compact Latent Flow-Matching Model for Stochastic Weather Forecasting
Arsen Kuzhamuratov ⋅ Mikhail Zhirnov ⋅ Konstantin Sobolev
COSMOS: Soft Mechanism Mixtures with Verifiable Routing for Long-Horizon PDE Forecasting
Anupam Rawat ⋅ Manikandan Padmanaban ⋅ Jagabondhu Hazra
In-Context Learning of Hidden Markov Models by Loop Transformers
Minseop Shin ⋅ Jaeyoung Cha ⋅ Chulhee Yun
Global Transport Couplings for Classifier-Free Guided Flows
Katarina Petrović ⋅ Zander Blasingame ⋅ Danyal Rehman ⋅ Ismail Ilkan Ceylan ⋅ Michael Bronstein ⋅ Stephen Zhang ⋅ Lazar Atanackovic ⋅ Alexander Tong
Gaussian Flow Dynamics: Stochastic Processes with Gaussian Marginal Laws
Grigory Bartosh ⋅ Christian Andersson Naesseth
Steering Diffusion Models to Rare Events with Sequential Monte Carlo
Aavash Subedi ⋅ Tim Reichelt ⋅ Christopher Williams ⋅ Philip Stier ⋅ Yee Whye Teh ⋅ Saifuddin Syed
Sequential Set Prediction from Stochastic Fluorophore Blinking: Supervision and Architecture in SMLM
Fatemeh Valeh ⋅ Mónika Farsang ⋅ Radu Grosu ⋅ Gerhard Schütz
Sketch-Conditioned Local Protein Backbone Redesign
Lingrong Zhang ⋅ Bingxin Zhou ⋅ Andi Han ⋅ Liang Hong
StochLOB: Heavy-Tailed Score Matching for Robust Limit Order Book Trend Prediction
Arshia Abolghasemi ⋅ seyedreza tavakoli ⋅ Parsa Naderi ⋅ Nazanin Mirzaei ⋅ Behrad Jahani ⋅ Saba Yousefzade ⋅ tahereh Javaheri ⋅ Mohammad Hossein Rohban ⋅ Marjan Alirezaie ⋅ Gholamali Aminian ⋅ Ali Habibnia
Same Sample or Fresh? The Coupling Geometry of Stochastic Extragradient
Xiaoyu Li ⋅ Dai Shi ⋅ Jiaojiao Jiang ⋅ Junbin Gao ⋅ Andi Han
SHIFT: Stochastic Hidden-Trajectory Deflection for Removing Diffusion-based Watermarks
Rui Bao ⋅ Zheng Gao ⋅ Xiaoyu Li ⋅ Xiaoyan Feng ⋅ Yang Song ⋅ Jiaojiao Jiang
Free Reward Tilting via Embedding Diffusion
Rafal Karczewski ⋅ Peter Blohm ⋅ Markus Heinonen ⋅ Vikas Garg
TreeSBM: Tree-Valued Schrödinger Bridges for Protein Evolution Forecasting
Navya Nori ⋅ Elizabeth H Mahood ⋅ Kimberly Liang ⋅ Pranam Chatterjee
Scalable Gaussian Process Flows
Tom Cowperthwaite ⋅ Henry Moss ⋅ Lachlan Astfalck ⋅ Louis Sharrock
SADGE: Spatially-Adaptive Diffusion Guided by Estimated Degradation for Image Restoration
Dominik Galus ⋅ Michał Furgała ⋅ Piotr Ryszko ⋅ Wojciech M Kozłowski
Risk-Calibrated Proposal Transport for Finite-Particle Diffusion Steering
Ziseok Lee ⋅ Jaehyeon Kim ⋅ Seungwon Kim ⋅ Seunghyun Moon ⋅ Haneul Choi ⋅ Wooyeol Lee ⋅ Minhyeong Lee ⋅ Kyungsu Kim
Correlated Randomness in Diffusion Simulation of Full Collider Response
Junzhe Liu ⋅ Eric Reinhardt ⋅ Ruchi Chudasama ⋅ Sergei Gleyzer
Attention Kernels for Learning Maps Between Heavy-Tailed Measures
Kailen Hargenrader ⋅ Bohan Chen ⋅ Edoardo Calvello
One for All, All for One: Coordinated Multi-Agent Diffusion Steering via Stochastic Optimal Control
Riccardo Barbano ⋅ Vincent Pauline ⋅ Runchang Li ⋅ George Webber ⋅ Alexander Denker ⋅ Željko Kereta ⋅ Stefan Bauer ⋅ Francisco Vargas ⋅ Esmeralda S Whitammer
Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning
Mar Gonzàlez I Català ⋅ Haitz Sáez de Ocáriz Borde ⋅ Davide Murari ⋅ Carola-Bibiane Schönlieb ⋅ Pietro Lió ⋅ George D Montañez
Physics is the Best Teacher: Consistency Learning for Time-Invariant Operators of Chaotic Dynamics
Lufang Chiang ⋅ Jiachen Yao ⋅ Thomas YL Lin ⋅ Animashree Anandkumar
Backward-Consistent Diffusion Sampling for Sparsely Observed PDE Inverse Problems
Yida Pan ⋅ Muhammad H Ashiq ⋅ Chanyong Jung ⋅ Yixuan Jia ⋅ Jonah Miller ⋅ Ismail Alkhouri ⋅ Qing Qu
Perturb-and-Solve: Efficient Learned-Operator Conditioning for Latent Diffusion Inverse Problems
Abduragim Shtanchaev ⋅ Arip Asadulaev ⋅ Luiza Labazanova ⋅ Aidar Alimbayev ⋅ Karim Salta ⋅ Eric Moulines ⋅ Martin Takac
Noise, Denoise, Correct: MCMC Posterior Sampling with Diffusion Priors in Three Steps
So Takao ⋅ Gregory Bellchambers ⋅ Luke Ye ⋅ Sanmitra Ghosh ⋅ Michalis Michaelides
STARRY-NET: A Neuro-Symbolic Model for Time Series Forecasting
Haoyun Wu ⋅ Pablo Montero-Manso ⋅ Steve Thomas ⋅ Trung H Le ⋅ Weijie Shen ⋅ Kenneth C Lichtendahl ⋅ Chris Fry
LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery
Binglin Ji ⋅ Anindya Sarkar ⋅ Hengchang Lu ⋅ Lecheng Kong ⋅ Yixin Chen ⋅ Yevgeniy Vorobeychik
ANCHOR: Safe Diffusion Planning via Analytic Approximation of Doob's $h$-function
Carlo Kneissl ⋅ Lorenzo Mazza ⋅ Stefanie Speidel ⋅ Gitta Kutyniok
Error-Conditioned Neural Solvers
Haina Jiang ⋅ Liam J. Wang ⋅ Peng-Chen Chen ⋅ Min-Seop Kwak ⋅ Seungryong Kim ⋅ Brian W Bell ⋅ Jeong Joon Park
Steered Not Stirred: Effective Tilting in Generative Models using Surrogate Reward Mixing
Alec Sargood ⋅ Olivia Gallup ⋅ Georg Maierhofer ⋅ Noam Ghenassia ⋅ Paul Duckworth ⋅ Krisztina Sinkovics ⋅ Joey Bose
Diffusion on Hyperbolic Space with a Curvature Determined Confinement
Prithika Narayanan ⋅ Daria Godorozha ⋅ Mateusz Mikolajczak ⋅ Aditya K Shethwala
SDECast: Probabilistic Weather Forecasting in Continuous Time with Neural SDEs
Maria Marchenko ⋅ Martin Andrae ⋅ Fredrik Lindsten ⋅ Christian Andersson Naesseth
Towards Understanding LLM Latent Inference through Fuzzy Reasoning Dynamics Modeling
Fusheng Li ⋅ Hao Wu ⋅ Wangli Yang ⋅ Wanqing Li ⋅ Wenbin Zhang ⋅ Yi Guo ⋅ Jie Yang
Mirror Bridges Between Probability Measures
Leticia M Da Silva ⋅ Silvia Sellán ⋅ Francisco Vargas ⋅ Justin Solomon
Conditioning Stochastic Processes using Guided Latent Dynamics
Louis Sharrock ⋅ Henry Moss ⋅ Lachlan Astfalck
Improved Training of Strong Stochastic Flow Maps
Zander Blasingame ⋅ Antonio Franca ⋅ Niklas Rindtorff ⋅ Alexander Tong
Zero Flux: Flow-Based Comparison of High-Dimensional Discrete Distributions
Leyang Wang ⋅ Yakun Wang ⋅ Song Liu ⋅ Taiji Suzuki