Jan-Willem van de Meent

Associate professor (UHD)
AMLab and Delta Lab
Informatics Institute
University of Amsterdam
Science Park, Lab 42, L4.13


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Dr. Jan-Willem van de Meent is an Associate Professor (Universitair Hoofddocent) at the University of Amsterdam. He co-directs the AMLab with Max Welling and co-directs the Uva Bosch Delta Lab with Theo Gevers. He previously held a position as an Assistant Professor at Northeastern University, where he continues to co-advise and collaborate. Prior to becoming faculty at Northeastern, he held a postdoctoral position with Frank Wood at Oxford, as well as a postdoctoral position with Chris Wiggins and Ruben Gonzalez at Columbia University. He carried out his PhD research in biophysics at Leiden and Cambridge with Wim van Saarloos and Ray Goldstein.

Jan-Willem van de Meent’s group develops models for artificial intelligence by combining probabilistic programming and deep learning. A major theme in this work is understanding how we can develop data-efficient models in machine learning by incorporating knowledge of an underlying physical system, causal structure, or symmetries of the underlying domain. At a technical level, his group develops inference methods for probabilistic programming systems. He is one of the creators of Anglican, a probabilistic language based on Clojure and of Probabilistic Torch, a library for deep generative models that extends PyTorch. He is also an author on a forthcoming book on probabilistic programming, a draft of which is available on arXiv. To ground methodological work in practice, his group collaborates with researchers in neuroscience, NLP, healthcare, robotics, physics, and chemistry.

Jan-Willem van de Meent served as a founding co-chair of the international conference on probabilistic programming (PROBPROG). He is currently serving as a program chair for the international conference on artificial intelligence and statistics (AISTATS). He was the recipient of an NWO Rubicon Fellowship and of an NSF CAREER award.

Recent Publications


  1. ICLR
    Entropy Coding of Unordered Data Structures
    Kunze, Julius, Severo, Daniel, Zani, Giulio, van de Meent, Jan-Willem, and Townsend, James
    In International Conference on Learning Representations (ICLR) 2024


  1. EMNLP
    CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models
    McInerney, Denis Jered, Young, Geoffrey, Meent, Jan-Willem, and Wallace, Byron
    In The 2023 Conference on Empirical Methods in Natural Language Processing 2023
  2. NeurIPS
    Topological Obstructions and How to Avoid Them
    Esmaeili, Babak, Walters, Robin, Zimmermann, Heiko, and van de Meent, Jan-Willem
    In Thirty-seventh Conference on Neural Information Processing Systems (to appear) Dec 2023
  3. CoRL
    One-shot Imitation Learning via Interaction Warping
    Biza, Ondrej, Thompson, Skye, Pagidi, Kishore Reddy, Kumar, Abhinav, Pol, Elise, Walters, Robin, Kipf, Thomas, Meent, Jan-Willem, Wong, Lawson L.S., and Platt, Robert
    In 7th Annual Conference on Robot Learning Nov 2023
  4. ACT
    String Diagrams with Factorized Densities
    Sennesh, Eli, and van de Meent, Jan-Willem
    In Applied Category Theory Jul 2023
    Entropy Coding of Unordered Data Structures
    Kunze, Julius, Severo, Daniel, Zani, Giulio, Meent, Jan-Willem, and Townsend, James
    In ICML 2023 Workshop Neural Compression: From Information Theory to Applications Jul 2023
  6. TMLR
    A Variational Perspective on Generative Flow Networks
    Zimmermann, Heiko, Lindsten, Fredrik, Meent, Jan-Willem, and Naesseth, Christian A
    Transactions on Machine Learning Research Apr 2023
  7. LAFI
    Verified Reversible Programming for Verified Lossless Compression
    Townsend, James, and van de Meent, Jan-Willem
    In POPL Workshop on Languages for Inference (LAFI) Apr 2023
  8. LAFI
    A convenient category of tracing measure kernels
    Sennesh, Eli, and van de Meent, Jan-Willem
    In POPL Workshop on Languages for Inference (LAFI) Apr 2023
  9. LAFI
    Semantics of Probabilistic Program Traces
    Lew, Alexander, Sennesh, Eli, van de Meent, Jan-Willem, and Mansinghka, Vikash
    In POPL Workshop on Languages for Inference (LAFI) Apr 2023


  1. EMNLP
    That’s the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data
    McInerney, Denis Jered, Young, Geoffrey, van de Meent, Jan-Willem, and Wallace, Byron C.
    Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing Dec 2022
  2. NeurIPS WSGNR
    Understanding Optimization Challenges when Encoding to Geometric Structures
    Esmaeili, Babak, Walters, Robin, Zimmermann, Heiko, and Meent, Jan-Willem
    In NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations Dec 2022
  3. PLOS Comp Bio
    Probabilistic Program Inference in Network-Based Epidemiological Simulations
    Smedemark-Margulies, Niklas, Walters, Robin, Zimmermann, Heiko, Laird, Lucas, Loo, Christian, Kaushik, Neela, Caceres, Rajmonda, and Meent, Jan-Willem
    PLOS Computational Biology Nov 2022
  4. Bio. Pysch.
    Interoception as Modeling, Allostasis as Control
    Sennesh, Eli, Theriault, Jordan, Brooks, Dana, Meent, Jan-Willem, Barrett, Lisa Feldman, and Quigley, Karen S.
    Biological Psychology Nov 2022
  5. Neuroinf.
    A Computational Neural Model for Mapping Degenerate Neural Architectures
    Khan, Zulqarnain, Wang, Yiyu, Sennesh, Eli, Dy, Jennifer, Ostadabbas, Sarah, van de Meent, Jan-Willem, Hutchinson, J. Benjamin, and Satpute, Ajay B.
    Neuroinformatics Mar 2022
  6. WACV
    Enhancing Few-Shot Image Classification With Unlabelled Examples
    Bateni, Peyman, Barber, Jarred, Meent, Jan-Willem, and Wood, Frank
    In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Jan 2022


    Rate-Regularization and Generalization in Variational Autoencoders
    Bozkurt, Alican, Esmaeili, Babak, Tristan, Jean-Baptiste, Brooks, Dana, Dy, Jennifer, and Meent, Jan-Willem
    In International Conference on Artificial Intelligence and Statistics Mar 2021
  2. UAI
    Learning proposals for probabilistic programs with inference combinators
    Stites, Sam, Zimmermann, Heiko, Wu, Hao, Sennesh, Eli, and Meent, Jan-Willem
    In Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence 27–30 jul 2021
  3. EMNLP
    Disentangling Representations of Text by Masking Transformers
    Zhang, Xiongyi, van de Meent, Jan-Willem, and Wallace, Byron
    In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing Nov 2021
  4. NAACL
    On the Impact of Random Seeds on the Fairness of Clinical Classifiers
    Amir, Silvio, van de Meent, Jan-Willem, and Wallace, Byron
    In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Jun 2021
  5. NeurIPS
    Nested Variational Inference
    Zimmermann, Heiko, Wu, Hao, Esmaeili, Babak, and Meent, Jan-Willem
    In Advances in Neural Information Processing Systems Jun 2021
  6. AAMAS
    Action Priors for Large Action Spaces in Robotics
    Biza, Ondrej, Wang, Dian, Platt, Robert, Meent, Jan-Willem, and Wong, Lawson L.S.
    In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems Jun 2021
  7. ICML
    Conjugate Energy-Based Models
    Wu*, Hao, Esmaeili*, Babak, Wick, Michael L, Tristan, Jean-Baptiste, and van de Meent, Jan-Willem
    In International Conference on Machine Learning Jun 2021