Accepted Papers
List of Papers
Note that only papers in the proceedings track are archived.
Proceedings Track
The proceedings can be found at https://proceedings.mlr.press/v327/.
| 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, Peter Frazier, 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 |
| 14 | Poster | Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise? Emanuel Sommer, Kangning Diao, Jakob Robnik, Uros Seljak, David Rügamer |
| 15 | Poster | Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning Emanuel Sommer, David Rügamer |
| 16 | Poster | Reinforced sequential Monte Carlo for amortised sampling Sanghyeok Choi, Sarthak Mittal, Víctor Elvira, Jinkyoo Park, Esmeralda S. Whitammer |
| 17 | Poster | Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces Arran Carter, Sanghyeok Choi, Kirill Tamogashev, Víctor Elvira, Esmeralda S. Whitammer |
| 18 | Poster | Conformal Cross-Modal Active Learning Huy Hoang Nguyen, Cédric Jung, Shirin Salehi, Tobias Glück, Anke Schmeink, Andreas Kugi |
