van de Meent, Jan-Willem

35 publications

ICLR 2026 CORDS - Continuous Representations of Discrete Structures Tin Hadži Veljković, Erik J Bekkers, Michael Tiemann, Jan-Willem van de Meent

TMLR 2026 Improving Local Explainability by Learning Causal Graphs from Data Daan Roos, Sebastian Gerwinn, Jan-Willem van de Meent, Sara Magliacane

ICLR 2026 Purrception: Variational Flow Matching for Vector-Quantized Image Generation Răzvan-Andrei Matișan, Vincent Tao Hu, Grigory Bartosh, Björn Ommer, Cees G. M. Snoek, Max Welling, Jan-Willem van de Meent, Mohammad Mahdi Derakhshani, Floor Eijkelboom

ICLR 2026 Riemannian Variational Flow Matching for Material and Protein Design Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Cong Liu, Max Welling, Jan-Willem van de Meent, Erik J Bekkers

ICML 2025 Controlled Generation with Equivariant Variational Flow Matching Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J Bekkers, Max Welling, Christian A. Naesseth, Jan-Willem Van De Meent

ICML 2025 Erwin: A Tree-Based Hierarchical Transformer for Large-Scale Physical Systems Maksim Zhdanov, Max Welling, Jan-Willem Van De Meent

ICML 2025 Exponential Family Variational Flow Matching for Tabular Data Generation Andrés Guzmán-Cordero, Floor Eijkelboom, Jan-Willem Van De Meent

ICLR 2024 Entropy Coding of Unordered Data Structures Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend

ICMLW 2024 Modeling Droplets Dynamics in Emulsions with Graph Neural Networks Giulio Ortali, Federico Toschi, Jan-Willem van de Meent

NeurIPS 2024 Practical Shuffle Coding Julius Kunze, Daniel Severo, Jan-Willem van de Meent, James Townsend

NeurIPS 2024 VISA: Variational Inference with Sequential Sample-Average Approximations Heiko Zimmermann, Christian A. Naesseth, Jan-Willem van de Meent

NeurIPS 2024 Variational Flow Matching for Graph Generation Floor Eijkelboom, Grigory Bartosh, Christian A. Naesseth, Max Welling, Jan-Willem van de Meent

TMLR 2023 A Variational Perspective on Generative Flow Networks Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A Naesseth

ICMLW 2023 Entropy Coding of Unordered Data Structures Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend

CoRL 2023 One-Shot Imitation Learning via Interaction Warping Ondrej Biza, Skye Thompson, Kishore Reddy Pagidi, Abhinav Kumar, Elise van der Pol, Robin Walters, Thomas Kipf, Jan-Willem van de Meent, Lawson L. S. Wong, Robert Platt

NeurIPS 2023 Topological Obstructions and How to Avoid Them Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent

ICLRW 2022 Binding Actions to Objects in World Models Ondrej Biza, Robert Platt, Jan-Willem van de Meent, Lawson L.S. Wong, Thomas Kipf

WACV 2022 Enhancing Few-Shot Image Classification with Unlabelled Examples Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood

ICML 2022 Learning Symmetric Embeddings for Equivariant World Models Jung Yeon Park, Ondrej Biza, Linfeng Zhao, Jan-Willem Van De Meent, Robin Walters

NeurIPSW 2022 Understanding Optimization Challenges When Encoding to Geometric Structures Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent

AISTATS 2021 Rate-Regularization and Generalization in Variational Autoencoders Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana Brooks, Jennifer Dy, Jan-Willem van de Meent

ICML 2021 Conjugate Energy-Based Models Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem Van De Meent

ICLRW 2021 Conjugate Energy-Based Models Hao Wu, Babak Esmaeili, Michael L Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent

NeurIPS 2021 Nested Variational Inference Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent

ICML 2020 Amortized Population Gibbs Samplers with Neural Sufficient Statistics Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem Van De Meent

NeurIPSW 2020 Generator Surgery for Compressed Sensing Jung Yeon Park, Niklas Smedemark-Margulies, Mara Daniels, Rose Yu, Jan-Willem van de Meent, PAul HAnd

NeurIPS 2020 Neural Topographic Factor Analysis for fMRI Data Eli Sennesh, Zulqarnain Khan, Yiyu Wang, J Benjamin Hutchinson, Ajay Satpute, Jennifer Dy, Jan-Willem van de Meent

AISTATS 2019 Structured Neural Topic Models for Reviews Babak Esmaeili, Hongyi Huang, Byron Wallace, Jan-Willem van de Meent

NeurIPS 2017 Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth N, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah Goodman, Pushmeet Kohli, Frank Wood, Philip Torr

NeurIPS 2016 Bayesian Optimization for Probabilistic Programs Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A Osborne, Frank Wood

AISTATS 2016 Black-Box Policy Search with Probabilistic Programs Jan-Willem van de Meent, Brooks Paige, David Tolpin, Frank D. Wood

ECML-PKDD 2015 Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs David Tolpin, Jan-Willem van de Meent, Brooks Paige, Frank D. Wood

AISTATS 2015 Particle Gibbs with Ancestor Sampling for Probabilistic Programs Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood

ECML-PKDD 2015 Probabilistic Programming in Anglican David Tolpin, Jan-Willem van de Meent, Frank D. Wood

AISTATS 2014 A New Approach to Probabilistic Programming Inference Frank D. Wood, Jan-Willem van de Meent, Vikash Mansinghka