ProbML 2026

Symposium on Probabilistic Machine Learning

(Previously Symposium on Advances in Approximate Bayesian Inference)

Co-located with ICML 2026 in South Korea

July 5, 2026

Venue: TBD

Photo by Larry Koester, CC BY 2.0, via Flickr

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. Links to the PDFs to follow.

Proceedings Track

Coming Soon.

Workshop Track

Coming Soon.

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