Accepted Papers
Accepted papers will be announced after the acceptance notification date (8 May 2026 for Proceedings and Workshop tracks, 1 April 2026 for Fast Track).
Please check back after these dates for the full list of accepted papers.
List of Papers
Note that only papers in the proceedings track are archived.
Proceedings Track
| No. | Remark | Paper |
|---|---|---|
| 1 | Poster | Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization Marshal Arijona Sinaga, Julien Martinelli, Samuel Kaski |
| 2 | Poster | Wavelet Conditional Neural Processes Junyu Xuan, Mengjing Wu |
| 3 | Poster | Universality of Singular Complexity for Hyvärinen Generalized Bayes: Exact Transfer in Gaussian Factor Analysis Manoj Saravanan, Rohit Kumar Salla |
| 4 | Poster | An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms Nils Grünefeld, Jes Frellsen, Christian Hardmeier |
| 5 | Poster | Causal Temporal Graphs for Counterfactual Validation of Temporal Link Prediction Aniq Ur Rahman, Justin Coon |
| 6 | Poster | Neural Stochastic Differential Equations on Compact State Spaces: Theory, Methods, and Application to Suicide Risk Modeling Malinda Lu, Yue-Jane Liu, Matthew K. Nock, Yaniv Yacoby |
| 7 | Poster | Conditionally Identifiable Latent Representation for Multivariate Time Series with Structural Dynamics Minkey Chang, Jae-Young Kim |
| 8 | Poster | When Individually Calibrated Models Become Collectively Miscalibrated Zhaohui Geoffrey Wang |
| 9 | Poster | Characterizing the Representational Capacity of Neural Processes Robin Young |
| 10 | Poster | CogFormer: Learn All Your Models Once Jerry M. Huang, Lukas Schumacher, Niek Stevenson, Stefan T. Radev |
| 11 | Poster | Identifiability, Fisher Information, and Amortized Inference for Heterogeneous Diffusion from Discrete-Time Noisy Observations Zhen Yuan Yeo |
| 12 | Poster | Heterogeneous Coupled Diffusion for Graph Generation with α-Stable Node Feature Noise Tang Chenyu, Ercan Engin Kuruoglu |
| 13 | Poster | Uncertainty Propagation Through Green's Kernels and Gaussian Process Inference Dynamics Chi-Jen Roger Lo, Joan Lasenby |
| 14 | Poster | RAMP: Recognition parametrisation by Amortised Message Passing Lior Fox, Kai Biegun, James Heald, Samo Hromadka, Arielle Rosinski, Maneesh Sahani |
| 15 | Poster | Intention Inference Under Execution Noise: Separating Aleatoric and Epistemic Uncertainty in Social Dilemmas Kival Mahadew, Jonathan P. Shock |
| 16 | Poster | Latent Semantic Regularization: Enhancing Semantic Integrity in Tabular Data Synthesis Saba Amiri, Carlijn Nijhuis, Eric Nalisnick, Adam Belloum, Sander Klous, Leon Gommans |
Workshop Track
| No. | Remark | Paper |
|---|---|---|
| 1 | Poster | Conformal Calibration from Unlabelled Pools Kianoosh Ashouritaklimi |
| 2 | Poster | Uniform Trajectory Bounds for Heavy-Tailed Stochastic Gradient Langevin Dynamics Rameez Raja |
| 3 | Poster | Ab-L3BO: Bayesian Optimization of Antibody Sequence Design with Large Language Models Eunna Huh, Seungjin Choi, Hyunjin Shin |
| 4 | Poster | Gradient Flow Sampler-based Distributionally Robust Optimization Zusen Xu, Jia-Jie Zhu |
| 5 | Poster | Unifying Diffusion Identities via Tweedie's Formula Jiayi Lin, Thang D Bui |
| 6 | Poster | Denoising Uncertainty via Gaussian Distributional Diffusion Models Noa Margeta, Jes Frellsen, Ignacio Peis |
| 7 | Poster | Latent Diffusion for Missing Data Alberte Heering Estad, Ignacio Peis, Jes Frellsen |
| 8 | Poster | Gaussian Process Latent Factor Regression for Low-Data, High-Dimensional Output Problems Edward T Stevenson, Mei Ting Mak, N. J. Mayne, Eric Wolf, Miles Cranmer |
| 9 | Poster | Best-of-Both-Worlds Multi-Dueling Bandits: Unified Algorithms for Stochastic and Adversarial Preferences under Condorcet and Borda Objectives S Akash, Pratik Gajane, Jawar Singh |
| 10 | Poster | Uncertainty quantification in neural network-based glucose prediction for diabetes Hai Siong Tan, Rafe McBeth |
| 11 | Poster | Joint Model and Data Sparsification via the Marginal Likelihood Alexander Timans, Thomas Möllenhoff, Christian A. Naesseth, Mohammad Emtiyaz Khan, Eric Nalisnick |
| 12 | Poster | A Bayesian perspective on learning to grok in-context examples Abdessamed Qchohi, Simone Rossi |
| 13 | Poster | Quit While You’re Ahead: Sequential Training Can Harm Simulation-Based Inference Kai Samaroo, Yunyi Shen, Robin J. Ryder, Tamara Broderick |
| 14 | Poster | Bayesian Belief Compression for Sequential Model Selection Zhaohui Geoffrey Wang |
| 15 | Poster | Leave No One Out: Mitigating Subpopulation Shift via Leave-One-Out Upsampling Alice ST Cheng, Brooks Paige |
| 16 | Poster | Diffusion-Driven State Space Models Jack Ruder, Michael Wojnowicz |
| 17 | Poster | Accelerating Discrete Langevin Samplers via Continuous Intermediates Guangyu Li, Ruqi Zhang |
| 18 | Poster | Local Thompson Sampling via Prompting for Bayesian Optimization with LLM Generators Shorya Sharma, Raul Astudillo |
| 19 | Poster | Hierarchical Bayesian Crowdsourcing with Item Difficulty Seong Woo Han, Ozan Adıgüzel, Bob Carpenter |
| 20 | Poster | Clustering with Composite Weighted g-Bregman Divergences Adel Mohammadpour, Mina Aminghafari |
| 21 | Poster | Probabilistic Inference for Boyant Model Weights Aleksanteri Sladek, Martin Trapp, Arno Solin |
| 22 | Poster | IDProbCover: Intrinsic-Dimension Adaptive Coverage for Pool-Based Active Learning Poojith thummala, Mohamed Abdelrazek |
| 23 | Poster | Prediction-Powered Active Testing Kianoosh Ashouritaklimi, Tom Rainforth, Francois Caron |
| 24 | Poster | Probabilistic Circuit Networks Florian Peter Busch, Moritz Willig, Kristian Kersting, Devendra Singh Dhami |
| 25 | Poster | Neural Discrete Controlled Monte Carlo Samplers Sujong Lee, Pascal Jutras Dube, Bihan Wen, Ruqi Zhang |
| 26 | Poster | Self-Supervised Variational Priors for Robust Bayesian Inference Erik Englesson, Iaroslav Melekhov, Juho Kannala, Hossein Azizpour |
| 27 | Poster | Data-Driven Priors for Uncertainty-Aware Deterioration Risk Prediction with Multimodal Data Leopoldo Julian Lechuga Lopez, Tim G. J. Rudner, Farah E. Shamout |
| 28 | Poster | Uncertainty-Aware Modeling of Continuous-Time Interacting Systems via Relational Flows YongKyung Oh |
Fast Track
Not archived.
| No. | Remark | Paper |
|---|---|---|
| 1 | Poster | From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner, Lorenz Richter, Marcin Sendera, Jarrid Rector-Brooks, Nikolay Malkin |
| 2 | Poster | JAPAN: Joint Adaptive Prediction Areas with Normalising-flows Eshant English, Christoph Lippert |
| 3 | Poster | Post-hoc Probabilistic Vision-Language Models Anton Baumann, Rui Li, Marcus Klasson, Santeri Mentu, Shyamgopal Karthik, Zeynep Akata, Arno Solin, Martin Trapp |
| 4 | Poster | Federated ADMM from Bayesian Duality Thomas Moellenhoff, Siddharth Swaroop, Finale Doshi-Velez, Mohammad Emtiyaz Khan |
| 5 | Poster | Amortising Inference and Meta-Learning Priors in Neural Networks Tommy Rochussen, Vincent Fortuin |
| 6 | Poster | Do-PFN: In-Context Learning for Causal Effect Estimation Jake Robertson, Arik Reuter, Siyuan Guo, Noah Hollmann, Frank Hutter, Bernhard Schölkopf |
| 7 | Poster | Anytime-valid, Bayes-assisted, Prediction-Powered Inference Valentin Kilian, Stefano Cortinovis, François Caron |
| 8 | Poster | In-Context Learning of Stochastic Differential Equations with Foundation Inference Models Patrick Seifner, Kostadin Cvejoski, David Berghaus, César Ali Ojeda Marin, Ramsés J. Sánchez |
| 9 | Poster | In-Context Learning of Temporal Point Processes with Foundation Inference Models David Berghaus, Patrick Seifner, Kostadin Cvejoski, Cesar Ojeda, Ramses J Sanchez |
| 10 | Poster | Amortized In-Context Mixed Effect Transformer Models: A Zero-Shot Approach for Pharmacokinetics Cesar Ojeda, Niklas Hartung, Wilhelm Huisinga, Ramses J Sanchez |
| 11 | Poster | On the Interplay of Priors and Overparametrization in Bayesian Neural Network Posteriors Julius Kobialka, Emanuel Sommer, Chris Kolb, Juntae Kwon, Daniel Dold, David Rügamer |
| 12 | Poster | A Continuous-Time Markov Chain Framework for Insertion Language Models Dhruvesh Patel, Benjamin Rozonoyer, Soumitra Das, Tahira Naseem, Tim G. J. Rudner, Andrew McCallum |
| 13 | Poster | Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation Bohan Wu, David Blei |