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Workshop

Structured Probabilistic Inference and Generative Modeling

Dinghuai Zhang ⋅ Yuanqi Du ⋅ Guan-Horng Liu ⋅ Chenlin Meng ⋅ Ruiqi Gao ⋅ Max Welling ⋅ Yoshua Bengio
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Abstract

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Schedule

Timezone: Asia/Seoul
4:00 PM
Opening Remarks
Improving GFlowNets for Text-to-Image Diffusion Alignment
Dinghuai Zhang ⋅ Yizhe Zhang ⋅ Jiatao Gu ⋅ Ruixiang ZHANG ⋅ Joshua M Susskind ⋅ Navdeep Jaitly ⋅ Shuangfei Zhai
Lifted Residual Score Estimation
Tejas Jayashankar ⋅ Jongha (Jon) Ryu ⋅ Xiangxiang Xu ⋅ Gregory Wornell
Discrete Diffusion Posterior Sampling for Protein Design
Mert Cemri ⋅ Ajil Jalal ⋅ Kannan Ramchandran
SOLMformer - Incorporating Sequence and Observation Level Metadata for Categorical Time Series Modeling
Yamini Ananth ⋅ Gregory Benton ⋅ Jingxing Fang ⋅ Jerry Cheung ⋅ Xu Chu ⋅ Cong Yu
Improving Consistency Models with Generator-Induced Coupling
Thibaut Issenhuth ⋅ Ludovic Dos Santos ⋅ Jean-Yves Franceschi ⋅ alain rakotomamonjy
A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
Hamidreza Kamkari ⋅ Brendan Ross ⋅ Rasa Hosseinzadeh ⋅ Jesse Cresswell ⋅ Gabriel Loaiza-Ganem
All Roads Lead to Rome? Exploring Representational Similarities Between Latent Spaces of Generative Image Models
Charumathi Badrinath ⋅ Usha Bhalla ⋅ Alex Oesterling ⋅ Suraj Srinivas ⋅ Himabindu Lakkaraju
Bayesian Disease Progression Modeling That Captures And Accounts For Health Disparities
Erica Chiang ⋅ Ashley Beecy ⋅ Gabriel Sayer ⋅ Nir Uriel ⋅ Deborah Estrin ⋅ Nikhil Garg ⋅ Emma Pierson
Conformalized Credal Set Predictors
Alireza Javanmardi ⋅ David Stutz ⋅ Eyke Hüllermeier
Teaching dark matter simulations to speak the halo language
Shivam Pandey ⋅ Francois Lanusse ⋅ Chirag Modi ⋅ Benjamin Wandelt
DiMViS: Diffusion-based Multi-View Synthesis
Giuseppe Di Giacomo ⋅ Giulio Franzese ⋅ Tania Cerquitelli ⋅ Carla Fabiana Chiasserini ⋅ Pietro Michiardi
Reliability Thresholds for the Bethe Free Energy Approximation
Harald Leisenberger ⋅ Christian Knoll ⋅ Franz Pernkopf
Bidirectional Consistency Models
Liangchen Li ⋅ Jiajun He
Learnability of Parameter-Bounded Bayes Nets
Arnab Bhattacharyya ⋅ Davin Choo ⋅ Sutanu Gayen ⋅ Dimitrios Myrisiotis
Transformer Neural Autoregressive Flows
Massimiliano Patacchiola ⋅ Aliaksandra Shysheya ⋅ Katja Hofmann ⋅ Richard E Turner
Continual Deep Learning on the Edge via Stochastic Local Competition among Subnetworks
Theodoros Christophides ⋅ Kyriakos Tolias ⋅ Sotirios Chatzis
Rule-Enhanced Graph Learning
Ali ⋅ Abdolreza Mirzaei ⋅ Majjid Farhadi ⋅ Parmis Naddaf ⋅ Kiarash Zahirnia ⋅ Mohammad Salameh ⋅ Kevin Cannons ⋅ Richard Mar ⋅ Mingyi Wu ⋅ Oliver Schulte
Assessing the Viability of Generative Modeling in Simulated Astronomical Observations
Patrick Janulewicz ⋅ Laurence Perreault-Levasseur ⋅ Tracy Webb
Stein Variational Newton Neural Network Ensembles
Klemens Flöge ⋅ Muhammad Abdul Moeed ⋅ Vincent Fortuin
Diffusion Domain Expansion: Learning to Coordinate Pre-Trained Diffusion Models
Egor Lifar ⋅ Semyon Savkin ⋅ Timur Garipov ⋅ Shangyuan Tong ⋅ Tommi Jaakkola
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
Yuanqi Du ⋅ Michael Plainer ⋅ Rob Brekelmans ⋅ Chenru Duan ⋅ Frank Noe ⋅ Carla Gomes ⋅ Alan Aspuru-Guzik ⋅ Kirill Neklyudov
Collective Variable Free Transition Path Sampling with Generative Flow Network
Kiyoung Seong ⋅ Seonghyun Park ⋅ SEONGHWAN KIM ⋅ Woo Youn Kim ⋅ Sungsoo Ahn
QGFN: Controllable Greediness with Action Values
Elaine Lau ⋅ Stephen Lu ⋅ Ling Pan ⋅ Doina Precup ⋅ Emmanuel Bengio
Energy-Free Guidance of Geometric Diffusion Models for 3D Molecule Inverse Design
Sanjay Nagaraj ⋅ Aksh Garg ⋅ Jiaqi Han ⋅ Minkai Xu ⋅ Stefano Ermon
Informed Meta-Learning
Katarzyna Kobalczyk ⋅ Mihaela van der Schaar
Neurosymbolic Markov Models
Lennert De Smet ⋅ Gabriele Venturato ⋅ Luc De Raedt ⋅ Giuseppe Marra
In-Context Learning with Topological Information for LLM-Based Knowledge Graph Completion
Udari Sehwag ⋅ Kassiani Papasotiriou ⋅ Jared Vann ⋅ Sumitra Ganesh
Glauber Generative Model: Discrete Diffusion Models via Binary Classification
Harshit Varma ⋅ Dheeraj Nagaraj ⋅ Karthikeyan Shanmugam
ProxyTune: Hyperparameter tuning through iteratively refined proxies
Agrin Hilmkil ⋅ Wenbo Gong ⋅ Nick Pawlowski ⋅ Cheng Zhang
Fast yet Safe: Early-Exiting with Risk Control
Metod Jazbec ⋅ Alexander Timans ⋅ Tin Hadži Veljković ⋅ Johann Sakmann ⋅ Dan Zhang ⋅ Christian Andersson Naesseth ⋅ Eric Nalisnick
EigenVI: score-based variational inference with orthogonal function expansions
Diana Cai ⋅ Chirag Modi ⋅ Charles Margossian ⋅ Robert Gower ⋅ David Blei ⋅ Lawrence Saul
GLAD: Improving Latent Graph Generative Modeling with Simple Quantization
Van Khoa NGUYEN ⋅ Yoann Boget ⋅ Frantzeska Lavda ⋅ Alexandros Kalousis
Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
Patrick Pynadath ⋅ Riddhiman Bhattacharya ⋅ Arun Narayanan Hariharan ⋅ Ruqi Zhang
Test-Time Adaptation with State-Space Models
Mona Schirmer ⋅ Dan Zhang ⋅ Eric Nalisnick
MONGOOSE: Path-wise Smooth Bayesian Optimisation via Meta-learning
Adam Yang ⋅ Laurence Aitchison ⋅ Henry Moss
Cross-modality Matching and Prediction of Perturbation Responses with Labeled Gromov-Wasserstein Optimal Transport
Jayoung Ryu ⋅ Romain Lopez ⋅ Charlotte Bunne ⋅ Luca Pinello ⋅ Aviv Regev
RNA-FrameFlow for de novo 3D RNA Backbone Design
Rishabh Anand ⋅ Chaitanya Joshi ⋅ Alex Morehead ⋅ Arian Jamasb ⋅ Charles Harris ⋅ Simon Mathis ⋅ Kieran Didi ⋅ Bryan Hooi ⋅ Pietro Lió
Variance reduction of diffusion model's gradients with Taylor approximation-based control variate
Paul Jeha ⋅ Will Grathwohl ⋅ Michael Andersen ⋅ Carl Henrik Ek ⋅ Jes Frellsen
von Mises Quasi-Processes for Bayesian Circular Regression
Yarden Cohen ⋅ Alexandre Wu Navarro ⋅ Jes Frellsen ⋅ Richard E Turner ⋅ Raziel Riemer ⋅ Ari Pakman
Equivariant Flow Matching for Molecular Conformer Generation
Majdi Hassan ⋅ Nikhil Shenoy ⋅ Jungyoon Lee ⋅ Hannes Stärk ⋅ Stephan Thaler ⋅ Dominique Beaini
Many-to-many Image Generation with Auto-regressive Diffusion Models
Ying Shen ⋅ Yizhe Zhang ⋅ Shuangfei Zhai ⋅ Lifu Huang ⋅ Joshua M Susskind ⋅ Jiatao Gu
Aligned Diffusion Models for Retrosynthesis
Najwa Laabid ⋅ Severi Rissanen ⋅ Markus Heinonen ⋅ Arno Solin ⋅ Vikas Garg
Scaling the Vocabulary of Non-autoregressive Models for Efficient Generative Retrieval
Ravisri Valluri ⋅ Akash Kumar Mohankumar ⋅ Kushal Dave ⋅ Amit Singh ⋅ Jian Jiao ⋅ Manik Varma ⋅ Gaurav Sinha
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Christian Toth ⋅ Christian Knoll ⋅ Franz Pernkopf ⋅ Robert Peharz
Structured Generations: Using Hierarchical Clusters to guide Diffusion Models
Jorge da Silva Gonçalves ⋅ Laura Manduchi ⋅ Moritz Vandenhirtz ⋅ Julia Vogt
Non-Parameteric Conformal Distributionally Robust Optimization
Yash Patel ⋅ Guyang Cao ⋅ Ambuj Tewari
The GAN is dead; long live the GAN! A Modern Baseline GAN
Yiwen Huang ⋅ Aaron Gokaslan ⋅ Volodymyr Kuleshov ⋅ James Tompkin
Recursive Introspection: Teaching LLM Agents How to Self-Improve
Yuxiao Qu ⋅ Tianjun Zhang ⋅ Naman Garg ⋅ Aviral Kumar
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices
Nathaniel Cohen ⋅ Vladimir Kulikov ⋅ Matan Kleiner ⋅ Inbar Huberman-Spiegelglas ⋅ Tomer Michaeli
Transformers with Stochastic Competition for Tabular Data Modelling
Andreas Voskou ⋅ Charalambos Christoforou ⋅ Sotirios Chatzis
Learning Graph Neural Networks from Biased Outcome Data
Sidhika Balachandar ⋅ Shuvom Sadhuka ⋅ Bonnie Berger ⋅ Emma Pierson ⋅ Nikhil Garg
Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity
Charlie Hou ⋅ Kiran Thekumparampil ⋅ Michael Shavlovsky ⋅ Giulia Fanti ⋅ Sujay Sanghavi
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
Wasu Top Piriyakulkij ⋅ Yingheng Wang ⋅ Volodymyr Kuleshov
CADO: Cost-Aware Diffusion Solvers for Combinatorial Optimization through RL fine-tuning
Deunsol Yoon ⋅ Hyungseok Song ⋅ Kanghoon Lee ⋅ Woohyung Lim
Variational Inference with Censored Gaussian Process Regressors
Andrea Karlova ⋅ Rishabh Kabra ⋅ Daniel Augusto de Souza ⋅ Brooks Paige
Amortized Probabilistic Detection of Communities in Graphs
Yueqi Wang ⋅ Yoonho Lee ⋅ Pallab Basu ⋅ Juho Lee ⋅ Yee-Whye Teh ⋅ Department of Statistics Liam Paninski ⋅ Ari Pakman
Quantifying Aleatoric and Epistemic Uncertainty: A Credal Approach
Paul Hofman ⋅ Yusuf Sale ⋅ Eyke Hüllermeier
Predictive Uncertainties Based on Proper Scoring Rules
Nikita Kotelevskii ⋅ Maxim Panov
Color Style Transfer with Modulated Flows
Maria Larchenko ⋅ Alexander Lobashev ⋅ Dmitry Guskov ⋅ Vladimir Palyulin
Improving GFlowNets with Monte Carlo Tree Search
Nikita Morozov ⋅ Daniil Tiapkin ⋅ Sergey Samsonov ⋅ Alexey Naumov ⋅ Dmitry Vetrov
Identifying latent state transition in non-linear dynamical systems
Çağlar Hızlı ⋅ Cagatay Yildiz ⋅ Matthias Bethge ⋅ ST John ⋅ Pekka Marttinen
Cell Morphology-Guided Small Molecule Generation with GFlowNets
Stephen Lu ⋅ Ziqing Lu ⋅ Ehsan Hajiramezanali ⋅ Tommaso Biancalani ⋅ Yoshua Bengio ⋅ Gabriele Scalia ⋅ Michał Koziarski
EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation
Yuqiao Wen ⋅ Behzad Shayegh ⋅ Chenyang Huang ⋅ Yanshuai Cao ⋅ Lili Mou
Simple and Effective Masked Diffusion Language Models
Subham Sekhar Sahoo ⋅ Marianne Arriola ⋅ Aaron Gokaslan ⋅ Edgar Marroquin ⋅ Alexander Rush ⋅ Yair Schiff ⋅ Justin Chiu ⋅ Volodymyr Kuleshov
Conditional Flow Matching for Time Series Modelling
Ella Tamir ⋅ Najwa Laabid ⋅ Markus Heinonen ⋅ Vikas Garg ⋅ Arno Solin
Accelerating NCE Convergence with Adaptive Normalizing Constant Computation
Anish Sevekari ⋅ Rishal Aggarwal ⋅ Maria Chikina ⋅ David Koes
Generative Design of Decision Tree Policies for Reinforcement Learning
Jacob Pettit ⋅ Chak Shing Lee ⋅ Jiachen Yang ⋅ Alex Ho ⋅ Daniel Faissol ⋅ Brenden Petersen ⋅ Mikel Landajuela
Learning Latent Graph Structures and their Uncertainty
Alessandro Manenti ⋅ Daniele Zambon ⋅ Cesare Alippi
Function Space Diversity for Uncertainty Prediction via Repulsive Last-Layer Ensembles
Sophie Steger ⋅ Christian Knoll ⋅ Bernhard Klein ⋅ Holger Fröning ⋅ Franz Pernkopf
Incorporating Stability Into Flow Matching
Christopher Iliffe Sprague ⋅ Arne Elofsson ⋅ Hossein Azizpour
Tuning-Free Alignment of Diffusion Models with Direct Noise Optimization
Zhiwei Tang ⋅ Jiangweizhi Peng ⋅ Jiasheng Tang ⋅ Mingyi Hong ⋅ Fan Wang ⋅ Tsung-Hui Chang
E-ProTran: Efficient Probabilistic Transformers for Forecasting
Batuhan Koyuncu ⋅ Tim N Bauerschmidt ⋅ Isabel Valera
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling
Jiatao Gu ⋅ Ying Shen ⋅ Shuangfei Zhai ⋅ Yizhe Zhang ⋅ Navdeep Jaitly ⋅ Joshua M Susskind
Demystifying amortized causal discovery with transformers
Francesco Montagna ⋅ Max Cairney-Leeming ⋅ Dhanya Sridhar ⋅ Francesco Locatello
Diffusion-based Episodes Augmentation for Offline Multi-Agent Reinforcement Learning
Jihwan Oh ⋅ Sungnyun Kim ⋅ Gahee Kim ⋅ SeongHwan Kim ⋅ Se-Young Yun
Analyzing GFlowNets: Stability, Expressiveness, and Assessment
Tiago Silva ⋅ Eliezer da Silva ⋅ Rodrigo Alves ⋅ Luiz Carvalho ⋅ Amauri Souza ⋅ Samuel Kaski ⋅ Vikas Garg ⋅ Diego Mesquita
Towards Dynamic Feature Acquisition on Medical Time Series by Maximizing Conditional Mutual Information
Fedor Sergeev ⋅ Paola Malsot ⋅ Gunnar Ratsch ⋅ Vincent Fortuin
Accelerating Best-of-N via Speculative Rejection
Ruiqi Zhang ⋅ Momin Haider ⋅ Ming Yin ⋅ Jiahao Qiu ⋅ Mengdi Wang ⋅ Peter Bartlett ⋅ Andrea Zanette
Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference
Xunpeng Huang ⋅ Difan Zou ⋅ Hanze Dong ⋅ Yi Zhang ⋅ Yian Ma ⋅ Tong Zhang
Generative Fractional Diffusion Models
Gabriel Nobis ⋅ Maximilian Springenberg ⋅ Marco Aversa ⋅ Michael Detzel ⋅ Rembert Daems ⋅ Roderick Murray-Smith ⋅ Shinichi Nakajima ⋅ Sebastian Lapuschkin ⋅ Stefano Ermon ⋅ Tolga Birdal ⋅ Manfred Opper ⋅ Christoph Knochenhauer ⋅ Luis Oala ⋅ Wojciech Samek
Stochastic Concept Bottleneck Models
Moritz Vandenhirtz ⋅ Sonia Laguna ⋅ Ričards Marcinkevičs ⋅ Julia Vogt
Exact Soft Analytical Side-Channel Attacks using Tractable Circuits
Thomas Wedenig ⋅ Rishub Nagpal ⋅ Gaëtan Cassiers ⋅ Stefan Mangard ⋅ Robert Peharz
Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani ⋅ Panagiotis Tigas ⋅ Stefan Bauer ⋅ Adam Foster
scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data
Moritz Vandenhirtz ⋅ Florian Barkmann ⋅ Laura Manduchi ⋅ Valentina Boeva ⋅ Julia Vogt
Learning high-dimensional mixed models via amortized variational inference
Priscilla Ong ⋅ Manuel Haussmann ⋅ Harri Lähdesmäki
Stabilizing the Training of Consistency Models with Score Guidance
Jeongjun Lee ⋅ Jonggeon Park ⋅ Jongmin Yoon ⋅ Juho Lee
Diffusion Models with Group Equivariance
Haoye Lu ⋅ Spencer Szabados ⋅ Yaoliang Yu
Disentangled Representation Learning through Geometry Preservation with the Gromov-Monge Gap
Théo Uscidda ⋅ Luca Eyring ⋅ Karsten Roth ⋅ Fabian Theis ⋅ Zeynep Akata ⋅ Marco Cuturi
Upper Error Bounds for Score-Based Inverse Problem Solving in Imaging
Irina Dobrianski ⋅ Dominik Narnhofer ⋅ Thomas Pock
Conformal Prediction for Time Series with Transformer
Junghwan Lee ⋅ Chen Xu ⋅ Yao Xie
Fine-Tuning with Uncertainty-Aware Priors Makes Vision and Language Foundation Models More Reliable
Tim G. J. Rudner ⋅ Xiang Pan ⋅ Yucen Li ⋅ Ravid Shwartz-Ziv ⋅ Andrew Wilson
Bayesian Reward Models for LLM Alignment
Adam Yang ⋅ Maxime Robeyns ⋅ Thomas Coste ⋅ zhengxiang shi ⋅ Jun Wang ⋅ Haitham Bou Ammar ⋅ Laurence Aitchison
Transferable Reinforcement Learning via Generalized Occupancy Models
Chuning Zhu ⋅ Xinqi Wang ⋅ Tyler Han ⋅ Simon Du ⋅ Abhishek Gupta
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Yair Schiff ⋅ Chia Hsiang Kao ⋅ Aaron Gokaslan ⋅ Tri Dao ⋅ Albert Gu ⋅ Volodymyr Kuleshov
A Practical Diffusion Path for Sampling
Lemir Omar Chehab ⋅ Anna Korba
From Graph Diffusion to Graph Classification
Jia Jun Cheng Xian ⋅ Seyed Mohammad Sadegh Mahdavi ⋅ Renjie Liao ⋅ Oliver Schulte
Generative Classifiers Avoid Shortcut Solutions
Alexander Li ⋅ Ananya Kumar ⋅ Deepak Pathak