UAI 2026

330 papers

Learning Lineage-guided Geodesics with Finsler Geometry

Aaron Zweig, Mingxuan Zhang, David A. Knowles, Elham Azizi

Towards Identifiability of Interventional Stochastic Differential Equations

Aaron Zweig, Zaikang Lin, Elham Azizi, David A. Knowles

Revisiting TD Target Aggregation under Uncertainty in Q-Learning

Lipeng Zu, Xiaonan Zhang

Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings

Yuqicheng Zhu, Nico Potyka, Bo Xiong, Trung-Kien Tran, Mojtaba Nayyeri

Unified Confidence Adjustment for Robust Cross-Modal Retrieval under Test-Time Distribution Shifts

Rui Zhou, Yawen Hao, Hao Zuo, Xinhang Wan, Cheng Zhu

Bandwidth Selection in Kernel Density Estimation for Model Calibration

Han Zhou, Teodora Popordanoska, Matthew B. Blaschko

Uncertainty Quantification of Click and Conversion Estimates for the Autobidding

Ivan Zhigalskii, Andrey Pudovikov, Aleksandr Katrutsa, Egor Samosvat

Self-Supervised Uncertainty Estimation For Super-Resolution of Satellite Images

Zhe Zheng, Valery Dewil, Pablo Arias

SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory

Xingtao Zhao, Hao Peng, Dingli Su, Xianghua Zeng, Chunyang Liu

Efficient Decentralized Learning of Generalized Quantal Response Equilibrium

Zehao Zhao, Apurv Shukla, Rahul Jain, Vijay G Subramanian

Gungnir: Exploiting Stylistic Features in Images for Backdoor Attacks on Diffusion Models

Lei Zhang, Yu Pan, Bingrong Dai, Lin Wang

Instrumental and Proximal Causal Inference with Gaussian Processes

Yuqi Zhang, Krikamol Muandet, Dino Sejdinovic, Edwin Fong, Siu Lun Chau

Not All Queries Need Deep Thought: CoFiCot for Adaptive Coarse-to-fine Stateful Refinement

Dongxu Zhang, Hongqiang Lin, Yiding Sun, Pengyu Wang, Qirui Wang

FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching

Haoran Zhang, Cainã Figueiredo Pereira, Marie Siew, Xutong Liu, Carlee Joe-Wong

Interpretable Causal Discovery via Causal-Effect Constraints

Cixuan Zhang, Guy Van den Broeck, Benjie Wang

Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness

Jonathan Zhang, Erik Skalnes, Jacob M. Chen, Michael Oberst

ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis

Zhanqi Zhang, Shun Li, Bernardo L. Sabatini, Mikio Christian Aoi, Gal Mishne

Structural Drift Repair in Decision Trees via Bayesian Model-Based Diagnosis

Yoav Zelinger, Meir Kalech

A Debiased LASSO Estimator for Design Matrices with Non-zero Mean Elements

Ashish Zantye, Ajit Rajwade, Radhendushka Srivastava

On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference

Moritz Akiya Zanger, Yijun Wu, Pascal R. van der Vaart, Wendelin Böhmer, Matthijs T. J. Spaan

Optimizing Likelihoods via Mutual Information: Bridging Simulation-Based Inference and Bayesian Optimal Experimental Design

Vincent D. Zaballa, Elliot E Hui

MMG: Mutual Information Estimation via the MMSE Gap in Diffusion

Longxuan Yu, Xing Shi, Xianghao Kong, Tong Jia, Greg Ver Steeg

Neural Value Iteration

Yang You, Ufuk \textÇakır, Alex Schutz, Nick Hawes

Estimating Interventional Outcomes over Time with Causal Normalizing Flow

Yoonseok Yeom, Jonghwan Kim, Taehui Yun, Juhyun Lyu, Jung-Hee Kim

When Can Transformers Count to n?

Gilad Yehudai, Haim Kaplan, Guy Dar, Royi Rassin, Asma Ghandeharioun

Near-Exponential Convergence Rates for kNN Classifications based on Boltzmann Margin

Luyuan Yang, Shayan Shafaei, Chao Lan

Evaluating the Role of Great Pre-trained Diffusion Models in Few-shot Phase: Warm-up and Acceleration

Ruofeng Yang, Yongcan Li, Bo Jiang, Cheng Chen, Shuai Li

Verbalizing LLM’s Higher-order Uncertainty via Imprecise Probabilities

Anita Yang, Krikamol Muandet, Michele Caprio, Siu Lun Chau, Masaki Adachi

ReVAD: From Imitation to Reasoning in Vectorized Autonomous Driving via Latent Space Search

Zhao Yang, Chengkang Duan, Weiyi Hu, Haoran Hu, Hua Cui

One-Shot Federated Learning based on Random Feature Extractor

Luyuan Yang, Shayan Shafaei, Yiming Liu, Naeem Shahabi Sani, Yu Cai

Robust Decision-Focused Learning via Worst-Case Regret Minimization

Shoki Yamao, Ken Kobayashi, Ryo Matsui, Shota Nagai, Naoki Nishimura

Vanilla SGD with Momentum Survives Heavy-Tailed Noise: Convergence Analysis without Gradient Clipping or Normalization

Ryusei Yamada, Naoki Sato, Hideaki Iiduka

Implicit Variational Rejection Sampling

Jian Xu, Shigui Li, Wei Chen, Jiacheng Li, Zhiqi Lin

Efficient Q-Learning and Actor–Critic Methods for Robust Average-Reward Reinforcement Learning.

Yang Xu, Swetha Ganesh, Vaneet Aggarwal

Kronecker-Structured Nonparametric Spatiotemporal Point Processes

Zhitong Xu, Qiwei Yuan, Yinghao Chen, Yan Sun, Bin Shen

How Learning Dynamics Drive Adversarially Robust Generalization?

Yuelin Xu, Xiao Zhang

Improving online FDR procedures via online analogs of e-closure and compound e-values

Ziyu Xu, Lasse Fischer, Aaditya Ramdas

ARGUS: Argumentation-Based Minimal-Change Repair for Verifiable LLM Self-Explanations

Yifan Xiao, Shijie Li

Federated Combinatorial Causal Bandits with Heterogeneous Causal Influences

Zheshun Wu, Wei Chen, Zenglin Xu, Fang Kong

DRL-ORA: Distributional Reinforcement Learning with Online Epistemic Risk Adaptation

Yupeng Wu, Wenyun Li, Wenjie Huang, Chin Pang Ho

Concept Sketching for Description Logics

Jinghan Wu, Chang Lu, Renate Schmidt, Yizheng Zhao

On the Convergence of Self-Improving Online LLM Alignment

Xudong Wu, Pangpang Liu, Vaneet Aggarwal, Jiayu Chen

Learning Representations from Perturbation: A Novel Matrix-View Weighting Framework for Naive Bayes

Siyao Wu, Huan Zhang, Kexin Meng, Zhipeng Ding, Pei Lv

An NTK Theory Approach to UCB Estimation in Semi-gradient TD Learning

Yijun Wu, Pascal R. van der Vaart, Moritz Akiya Zanger, Matthijs T. J. Spaan

Building a Bridge Between the Shapley Value, Prime Implicants and Counterfactual Explanations: a Theoretical Analysis

Hénoïk Willot

Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process Classification

Bernardo Williams, Harsha Vardhan Tetali, Arto Klami, Marcelo Hartmann

Single-Network Asymptotics for Causal Inference with Partial Network Data

Steven Wilkins-Reeves, Shane Lubold, Arun Chandrasekhar, Tyler Mccormick

Weighted Sequential Bayesian Inference for Non-Stationary Linear Contextual Bandits

Nicklas Werge, Yi-Shan Wu, Abdullah Akgül, Melih Kandemir

Efficient Federated Conformal Prediction with Group-Conditional Guarantee

Haifeng Wen, Osvaldo Simeone, Hong Xing

Hierarchical Bayesian Quadrature

Tim Weiland, Toni Karvonen, Philipp Hennig

Stationary Robust Mean-Field Games under Model Mismatches

Yue Wang

Graph Contrastive Learning with Low-Rank Regularization and Low-Rank Attention for Noisy Node Classification

Yancheng Wang, Ping Li, Yingzhen Yang

Bandit Learning for Online Scheduling with Immediate Decision

Zilong Wang, Yuhao Zhang, Zhewei Wei, Shuai Li

On the Effect of Sampling Diversity in Scaling LLM Inference

Tianchun Wang, Yuanzhou Chen, Zichuan Liu, Jonathan Light, Weiyang Liu

From Moves to Paths: A Hierarchical Framework for Trajectory Representation Learning

Chundong Wang, Xiangtian Zheng, Qingbo Hao, Yongxin Zhao, Yixuan Song

Recursive Fréchet Mean Estimation

Cheng Wang, Carlos J Soto

Set-based v.s. Distribution-based Representations of Epistemic Uncertainty: A Comparative Study

Kaizheng Wang, Yunjia Wang, Fabio Cuzzolin, David Moens, Hans Hallez

Learning Informative Attention Weights for Person Re-Identification

Yancheng Wang, Nebojsa Jojic, Yingzhen Yang

Upper entropy for 2-monotone lower probabilities

Tuan-Anh Vu, Sébastien Destercke, Frédéric Pichon

Collapse-Aware Regularization for Reliable Reasoning Under Distribution Shift

Quynh Vo, Cong-Duy T Nguyen

Markovian Compression: Looking to the Past Helps Accelerate the Future

Andrey Veprikov, Vladimir Solodkin, Mikhail Rudakov, Petr Babkin, Aleksandr Beznosikov

Structured Credal Learning

Varun Venkatesh, Eyke Hüllermeier, Bernd Bischl, Mina Rezaei

APIC: Amortized Physics-Informed Calibration using Neural Processes

Aishwarya Venkataramanan, Sai Karthikeya Vemuri, Joachim Denzler

Fisher8: Stabilizing Neural Heteroscedastic Regression via Output-Layer Fisher Geometry

Sumedh Vemuganti, Nickvash Kani

A Causal Markov Condition for Value

Olav Benjamin Vassend

Online Learning for Project Selection in Hedonic Project Games

Jaber Valizadeh, Dongmo Zhang, Omar Mubin, Ray Telikani

Improving TabPFN’s Synthetic Data Generation by Integrating Causal Structure

Davide Tugnoli, Andrea De Lorenzo, Marco Virgolin, Giovanni Cinà

Not Just How Much, But Where: Decomposing Epistemic Uncertainty into Per-Class Contributions

Mame Diarra Toure, David A. Stephens

Benign Overfitting with Quantum Kernels

Joachim Tomasi, Sandrine Anthoine, Hachem Kadri

On Pairwise Quantile Regression - Statistical Guarantees and Applications

Romain Therezien, Stéphan Clémençon, Fantin Girard, Hamza El-Abdouni

EVIA: Entropic Variational Inference Auto-encoding

Yunfei Teng, Zhichao Chen, Xinyu Chen, Lulu Tang, Sixin Zhang

Positive-Unlabeled Regression: learning from partially labeled quantitative outcomes

Paweł Teisseyre, Jan Mielniczuk

Robust and Computationally Efficient Linear Contextual Bandits under Adversarial Corruption and Heavy-Tailed Noise

Naoto Tani, Futoshi Futami

Particle Dynamics for Latent-Variable Energy-Based Models

Shiqin Tang, Shuxin Zhuang, Runsheng Yu, Rong Feng, Shujian Yu

Deep Spectral Learning of Embedded Latent Transfer Operators for Stochastic Dynamical Systems

Ryogo Tanaka, Yoshinobu Kawahara

Learning Who to Treat When Treatment is Missing

Johnna Sundberg, Rayid Ghani, Eli Ben-Michael, Edward Kennedy

Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent

Yihang Sun, Huaijin Wang, Patrick Hayden, Jose Blanchet

Possibilistic Instrumental Variable Regression with Potentially Invalid Instruments

Gregor Steiner, Jeremie Houssineau, Mark Steel

Multiwinner Voting with Interval Preferences under Incomplete Information

Drew Springham, Edith Elkind, Bart de Keijzer, Maria Polukarov

Privacy-Preserving Robustness Verification for Neural Networks

Nianyun Song, Xiaokun Luan, Yu Guo, Rongfang Bie, Meng Sun

Adaptive Fourier Decomposition-guided Neural Operator Design for Inverse PDE Problems

Zeyuan Song, Xiaocong Zhen, Zheyu Jiang

Consensus Optimization Graph Neural Networks

Olga Solodova, Ryan P Adams

Learning-based Optimal Admission Control for Erlang-B Queuing Systems

Shubhhi Singh, Shubhanshu Shekhar, Vijay G Subramanian

The Minimal Search Space for Conditional Causal Bandits

Francisco N. F. Q. Simoes, Itai Feigenbaum, Mehdi Dastani, Thijs van Ommen

Particle GFlowNets: Rethinking Generative Marginalization Models

Tiago da Silva, Diego Mesquita, Salem Lahlou

A Stronger Calculus of Intervention for Max-Linear Bayesian Networks

Leon Sierau, Francesco Nowell, Nihat Ay

Conditional neural control variates for variance reduction in Bayesian inverse problems

Ali Siahkoohi, Hyunwoo Oh

Collaborative Multi-view Learning from Crowds

Shanshan Si, Liangxiao Jiang, Wenjun Zhang, Chaoqun Li, Liangjun Yu

Fixed-Confidence Best-Arm Identification for Causal Mediation Analysis

Harsh Shrivastava, Yuta Kawakami, Junpei Komiyama, Jin Tian

Evaluation of "Probabilities of Causation" in Case-Control Studies: Identification and Estimation

Ryusei Shingaki, Haruka Yoshida, manabu kuroki

Valid and Efficient Uncertainty Quantification for Federated Joint Shift

Yuanjie Shi, Peihong Li, Xuanyu Cao, Yan Yan

Finding the Signal in the Spam: Jointly Learning Rewards and Worker Reliability from Pairwise Comparisons

Kaustubh Shivshankar Shejole, Tanish Agarwal, Arpit Agarwal, Avishek Ghosh

Improving TensorSketch Using Complex Random Variables

Amit Sharma, Mohammad Azhar Khan, Rameshwar Pratap, Keegan Kang

Analytic Planning under Uncertainty with Moment Closure

Shishir Sharma, Doina Precup

The Art of Calling the Winner by Asking Just Enough Questions

Nisarg Shah, Ziqi Yu

Birds of a Feather Reason Together: Gestalt Grouping Meets Neuro-Symbolic Inference

Jingyuan Sha, Hikaru Shindo, Kristian Kersting, Devendra Singh Dhami

Sign Identifiability of Causal Effects in Stationary Stochastic Dynamical Systems

Gijs van Seeventer, Saber Salehkaleybar

The Price of Knowledge: Optimal Algorithms for Costly Bandits

Felix Schur, Jesus Lago, Tanner Fiez

A Sobering Look at Tabular Data Generation via Probabilistic Circuits

Davide Scassola, Dylan Ponsford, Adrián Javaloy, Sebastiano Saccani, Luca Bortolussi

Global Convergence of Average Reward Constrained MDPs with Neural Critic and General Policy Parameterization

Anirudh Satheesh, Pankaj Kumar Barman, Washim Uddin Mondal, Vaneet Aggarwal