UAI 2026

330 papers

Quantized Stochastic Primal–Dual Methods for Distributed Optimization under Relaxed Global Geometry

Susmit Sarkar, Abhinav Raghuvanshi, Kushal Chakrabarti, Mayank Baranwal

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

Colin Samplawski, Ramneet Kaur, Manoj Acharya, Anirban Roy, Adam D. Cobb

Variance Reduction for Non-Log-Concave Sampling with Applications to Inverse Problems

M. Berk Sahin, Ahmet Ege Tanriverdi, Behzad Sharif, Abolfazl Hashemi

Fairness Uncertainty Quantification: A Constrained Stochastic Optimization Perspective

Abhishek Roy, Prasant Mohapatra

VaSST: Variational Inference for Symbolic Regression using Soft Symbolic Trees

Somjit Roy, Pritam Dey, Bani Mallick

Kernel Integrated R^2: A Measure of Dependence

Pouya Roudaki, Shakeel Gavioli-Akilagun, Florian Kalinke, Mona Azadkia, Zoltan Szabo

Constrained Weighted Bayesian Bootstrap

Sam Rosen, Jason Xu

Planning with Formal Reachability Guarantees in Goal-Oriented MDPs with Dead-Ends

Matisse Roche, Caroline P.C. Chanel, Yoko Watanabe

Imprecise Probabilities for Privacy–Accuracy Trade-offs in Bayesian Networks

Niccolò Rocchi, Fabio Stella, Cassio de Campos

Expert Advice with Costly Observations

Lev Reyzin, Aadirupa Saha, Shuo Wu

Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means

Raphaël Razafindralambo, Remy Sun, Damien Garreau, Frederic Precioso, Pierre-Alexandre Mattei

Structure Learning for Unfaithful Distributions: The Minimal Dependence Faithfulness

Pouria Ramazi, Hamid Kalantari

Variance Estimation and Selecting Good Estimands for Causal Effect Queries

Anna K Raichev, Rina Dechter, Jin Tian, Alexander Ihler

Metacognitive Arbitration as Uncertainty Compression in Multi-Agent Language Models

Mafizur Rahman, Lijun Qian

Beyond Mean-Field: Tree-Copula Variational Autoencoders for Structured Latent Dependencies

Yarden Rachamim, Shai Fine

Multi-Agent RL with Invisible Collaborators: Marginal Advantage Estimation for Indirect Cooperation

Jianglin Qiao, Zehong Cao, Siyi Hu, Mingjun Fan, Mahardhika Pratama

Reading As Humans: Unified Negation Detection via Cascade Linear Attention Network with Model-Agnostic Meta-Learning

Zhong Qian, Peifeng Li, Qiaoming Zhu, Guodong Zhou

Transformer Based Bayesian Network Structure Learning from an Information Theory Perspective

Zhiwei Qi, Kun Yue, Zhu Yang, Jiahui Wang

Distributional Deep Gaussian Processes

Sebastian Popescu

UnGuide: Learning to Forget with LoRA-Guided Diffusion Models

Alicja Polowczyk, Agnieszka Polowczyk, Dawid Malarz, Artur Kasymov, Jacek Tabor

A Characterization of the Orthocomplement of the Tangent Space of Semiparametric Markov Models

Trung Q. Phung, Ilya Shpitser

Semantic Self-Distillation for Language Model Uncertainty

Edward Phillips, Sean Wu, Fredrik K. Gustafsson, Boyan Gao, David A. Clifton

Bayesian Experimental Design via Score Matching

Angus Phillips, Gavin Kerrigan, Tom Rainforth

How Predicted Links Influence Network Evolution: Disentangling Choice and Algorithmic Feedback in Dynamic Graphs

Mathilde Perez, Raphaël Romero, Jefrey Lijffijt, Charlotte Laclau

Information Theoretic Bayesian Optimization over the Probability Simplex

Federico Pavesi, Antonio Candelieri, Noémie Jaquier

Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities

Richard D. Paul, Anton Stratmann, Johann F. Jadebeck, Martin Beyß, Hanno Scharr

Breaking Bad: Component-Wise Parent Deletion for Score-Based Causal Discovery

Min Woo Park, Taehui Yun, YoungIn Jang, Yoonseok Yeom, Jonghwan Kim

On Transportability for Structural Causal Bandits

Min Woo Park, Sanghack Lee

The Convergence Behavior of Adam under Heavy-Tailed Noise

Yijiang Pang

Explore, Refine, then Commit: Nearly Optimal Multi-Group Mean Estimation with Active Learning

Shourya Pandey, Syamantak Kumar

Sample-Efficient Learning of Probabilistic Causes for Reachability in Markov Decision Processes with Probabilistic Guarantees

Ryohei Oura, Georgios Fainekos, Hideki Okamoto, Bardh Hoxha

Coarsening Bias from Variable Discretization in Causal Functionals

Xiaxian Ou, Razieh Nabi

Partially Observed Structural Causal Models

Turan Orujlu, Jordan Kyle Matelsky, Martin V. Butz, Charley M Wu, Konrad Kording

Falsifying Causal Graphs With Outlier Events

William Roy Orchard, Philipp Michael Faller, Dominik Janzing

MetaCaDI: A Meta-Learning Framework for Causal Discovery from Multiple Environments with Unknown Interventions

Hans Jarett Ong, Yoichi Chikahara, Tomoharu Iwata

Prior-Fitted Functional Flows: In-Context Generative Models for Pharmacokinetics

César Ojeda, Niklas Hartung, Purity Kamene Kavwele, Tim Jahn, Piyush Kumar

What Type of Inference is Active Inference?

Wouter W. L. Nuijten, Mykola Lukashchuk, Thijs van de Laar, Bert de Vries

Conformal Risk Minimization with Variance Reduction

Sima Noorani, Orlando Romero, Nicolò Dal Fabbro, Hamed Hassani, George J. Pappas

Scaling Up Bayesian DAG Sampling

Daniele Nikzad, Alexander Zhilkin, Juha Harviainen, Jack Kuipers, Giusi Moffa

Mixture-Greedy for Online Generative Model Selection: Is UCB Necessary in Diversity-Aware Multi-Armed Bandits?

Bahar Dibaei Nia, Farzan Farnia

MUSS: Multilevel Subset Selection for Relevance and Diversity

Vu Nguyen, Andrey Kan

When Does Model Multiplicity Affect Prediction Intervals? A Sharp Phase Transition

Hai Nguyen, Khanh Nguyen, Hung Mai, Luong Doan, Nhung Duong

Tight rates of approximation of mixed Nash equilibria by entropy regularization in continuous games

Khang Nguyen, Valentio Iverson, Sahan Wijetunga, William Chang, Guillaume Wang

REALITrees: Rashomon Ensemble Active Learning for Interpretable Trees

Simon Dovan Nguyen, Hayden McTavish, Kentaro Hoffman, Tyler Mccormick, Cynthia Rudin

Adaptive and Robust Watermark for Generative Tabular Data

Dung Daniel Ngo, Archan Ray, Akshay Seshadri, Daniel Scott, Saheed Obitayo

What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty

Aran Nayebi

Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing

Adhyyan Narang, Sarah Dean, Lillian J. Ratliff, Maryam Fazel

IDCR: Information-Directed Conformal Retrieval

Manas Nanivadekar, Jatin Khanijoan, Swayam Kothekar, Mohd Amaan Khan

Online Bootstrap Inference for the Trend of Nonstationary Time Series

Thomas Nagler, Tobias Brock, Nicolai Palm

Model Agnostic Graph Prompt Learning for Crystal Property Prediction

Shrimon Mukherjee, Kishalay Das, Partha Basuchowdhuri, Pawan Goyal, Niloy Ganguly

Learning to Infer Fast by Attending to Sparse Temporal Observations

Mehrnaz Motamed, Harry Bendekgey, Debora Sujono, Erik B. Sudderth

Causal Reasoning with Bipartite Graphical Causal Models

Joris M. Mooij

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation

Eduardo Fernandes Montesuma, Yassir Bendou, Mike Gartrell

Learning Stable Digraphs from Sparse-Input Linear Structural Causal Models

Panagiotis Misiakos, Markus Püschel

Long term sequential decision making under risk

Mohammad Mirzanejad, Nadjet Bourdache, Abdel-Illah Mouaddib

Robust estimation of graphical models with measurement error: False discovery control and sensitivity analysis

Shira Mingelgrin, Y. Samuel Wang

Globally Optimal Multi-Object Tracking with Splitting and Merging

Mihaela Mihaylova, Jelle Piepenbrock, Johannes Textor

Exact Uncertainty Propagation via Gaussian Process Neurons

Qiuxian Meng, Yongyou Zhang

Conformal Graph Prediction with Z-Gromov Wasserstein Distances

Gabriel Melo, Thibaut de Saivre, Anna Calissano, Florence d’Alché-Buc

Causal Discovery in Mixtures of Populations

Bijan Mazaheri, Spencer L. Gordon, Yuval Rabani, Leonard Schulman

Relaxing Faithfulness with Intervention-Only Causal Discovery

Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler

Meta-Dependence in Conditional Independence Testing

Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler

Provable Guarantees For Robust Feature Selection in Sparse Linear Models in High-Dimensions

Deepak Maurya, Adarsh Barik, Jean Honorio

AudiFair: Privacy-Preserving Framework for Auditing Fairness

Elisaweta Masserova, Kshitij Kulkarni, Antigoni Polychroniadou, Ron D. Rothblum, Akira Takahashi

cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context

Jörg Martin, Stefan Haufe

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics

Joanna Marks, Tim Y. J. Wang, Omer Deniz Akyildiz

Learning plug-in surrogate endpoints for randomized experiments

Alessandro-Umberto Margueritte, Ahmet Zahid Balcıoğlu, Jesse H. Krijthe, Dave Zachariah, Fredrik D. Johansson

Information-Theoretic Lower Bounds for Causal Inference under Credal Uncertainty

Hung Mai, Hai Nguyen, Khanh Nguyen, Luong Doan, Nhung Duong

Approximating Nash Equilibria in Finite-Horizon Multi-Adversarial Team Markov Games

Prasanna Maddila, Régis Sabbadin, Meritxell Vinyals

Bayesian Causal Discovery in Directed Cyclic Graphs with Closed-Form Lag Bayes Factors

Seyed Reza Maadi, Sally Cripps

Learning Expressive Random Feature Models via Parametrized Activations

Zailin Ma, Jiansheng Yang, Yaodong Yang

First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints

Zhankun Luo, Antesh Upadhyay, Sang Bin Moon, Abolfazl Hashemi

The relative value of interventional and observational samples in Bayesian Causal Linear Gaussian Models

Valentinian Mihai Lungu, Anish Dhir, Mark van der Wilk, Ioannis Kontoyiannis

Computing Exact Nash Equilibria in Graphical Games: A Geometric Approach to Paths, Stars, and Caterpillars

Evan Lucca, Mohammad T. Irfan, Luis E. Ortiz

Conformal Prediction Sets for Instance Segmentation

Kerri Lu, Dan M. Kluger, Stephen Bates, Sherrie Wang

When Can We Learn from Noisy Logical Data? Parameterized Complexity of Approximate Concept Fitting in Description Logics

Chang Lu, Yizheng Zhao, Renate Schmidt

Score-Regularized Joint Sampling with Importance Weights for Flow Matching

Xinshuang Liu, Runfa Li, Shaoxiu Wei, Truong Nguyen

LENS: Latent Precision Inference in Multi-LLM Routing

Juntao Liu, Lixing Yu, Kun Yue, Zhiwen Tang

EagleConv: Bio-inspired Dual-Foveated Convolution for Robust Small Object Detection

Jianwei Liu, Lifei Hao, Baoqi Huang, Bing Jia, Xuandong Zhao

Constrained Random Forest for Domain-Generalizable Classification

Camilla Lingjærde, Geir Kjetil Sandve, Arnoldo Frigessi, Sylvia Richardson, Johan Pensar

Gradient-Guided Reward Optimization for Inference-time Alignment

Hankun Lin, Ruqi Zhang

Overcoming Dependent Censoring in the Evaluation of Survival Models

Christian Marius Lillelund, Shi-ang Qi, Russell Greiner

Grokked Models are Better Unlearners

Yuanbang Liang, Yang Li

HHC: Hierarchical Hypergraph Communication for Multi-Agent Systems

Qifan Liang, Chenlong Li, Feiyu Wang, Jing Fu, Yixiang Shan

Probabilistic Verification of Neural Networks via Efficient Probabilistic Hull Generation

Jingyang Li, Xin Chen, Hongfei Fu, Guoqiang Li

Exploiting Concavity Information in Contextual Bandit Optimization

Kevin Li, Eric Laber

Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement

Guoming Li, Jian Yang, Xukun Wang, Zixiao Wang, Shangsong Liang

Label-Wise uncertainty decomposition for Multi-label Classification by Maximizing Type II Likelihood

Minghao Li, Junjie Qiu, Weishi Shi

CAIC: Congestion-Aware Intent Communication for Multi-Agent Reinforcement Learning

Pei Li, Yongkang Zhang, Zhonglin Lv, Jinmin Zhu, Jiangjin Yin

A Sequence-Graph Fusion Framework via BiMamba and Fourier-KAN for Interpretable Drug-Target Affinity Prediction

Xibo Li, Lian Chen, Dingyuan Chen, Yichuan Zhao, Li Zhou

Online Fair Allocation with Demand-Side Time-Dependent Weight

Minming Li, Youzhi Zhang, Shangkun Zheng

Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach

Zihao Li, Fabrizio Russo

Matched-Pair Experimental Design with Active Learning

Weizhi Li, Gautam Dasarathy, Visar Berisha

Nonlinear Axiomatic Attribution for Cooperative Games

Weida Li, Zhuanghua Liu, Yaoliang Yu, Bryan Kian Hsiang Low

Differentially Private Approval-Based Committee Voting

Zhechen Li, Zimai Guo, Lirong Xia, Yongzhi Cao, Hanpin Wang

Computational Complexity of Repair Problems on Simple Temporal Networks with Uncertainty

Junkang Li, Frédéric Maris, Ajdin Sumic, Thierry Vidal, Bruno Zanuttini

Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation

Ilya Levin, Maksim Shuklin, Eric Moulines, Paul Mangold, Sergey Samsonov

Counting and Sampling Subsets Using Block Covers

Elias Lehtinen, Mikko Koivisto

Diagnosing Conformal Prediction Failures Under Distribution Shift: A COVID-19 Case Study

Chorok Lee

Preserving Compositionality for Robust Multi-Subject Personalization in Text-to-Image Generation

Sangho Lee, Eugene Baek, Suho Ryu, Dongsoo Shin, Joonseok Lee