Jan-Willem van de Meent

According to our database, Jan-Willem van de Meent authored at least 62 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Variational Flow Matching for Graph Generation.

Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent

CoRR, 2024

Inverse Concave-Utility Reinforcement Learning is Inverse Game Theory.

Mustafa Mert Çelikok, Frans A. Oliehoek, Jan-Willem van de Meent

CoRR, 2024

VISA: Variational Inference with Sequential Sample-Average Approximations.

Heiko Zimmermann, Christian A. Naesseth, Jan-Willem van de Meent

CoRR, 2024

Towards Reducing Diagnostic Errors with Interpretable Risk Prediction.

Denis Jered McInerney, William Dickinson, Lucy C. Flynn, Andrea Young, Geoffrey S. Young, Jan-Willem van de Meent, Byron C. Wallace

CoRR, 2024

Towards Reducing Diagnostic Errors with Interpretable Risk Prediction.

Denis Jered McInerney, William Dickinson, Lucy C. Flynn, Andrea Young, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Entropy Coding of Unordered Data Structures.

Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

A Variational Perspective on Generative Flow Networks.

Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A. Naesseth

Trans. Mach. Learn. Res., 2023

String Diagrams with Factorized Densities.

Eli Sennesh, Jan-Willem van de Meent

Proceedings of the Sixth International Conference on Applied Category Theory 2023, 2023

Topological Obstructions and How to Avoid Them.

Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models.

Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 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

Proceedings of the Conference on Robot Learning, 2023

2022

Probabilistic program inference in network-based epidemiological simulations.

Niklas Smedemark-Margulies, Robin Walters, Heiko Zimmermann, Lucas Laird, Christian van der Loo, Neela Kaushik, Rajmonda Caceres, Jan-Willem van de Meent

PLoS Comput. Biol., November, 2022

A Computational Neural Model for Mapping Degenerate Neural Architectures.

Zulqarnain Khan, Yiyu Wang, Eli Sennesh, Jennifer G. Dy, Sarah Ostadabbas, Jan-Willem van de Meent, J. Benjamin Hutchinson, Ajay B. Satpute

Neuroinformatics, 2022

Verified Reversible Programming for Verified Lossless Compression.

James Townsend, Jan-Willem van de Meent

CoRR, 2022

Binding Actions to Objects in World Models.

Ondrej Biza, Robert Platt, Jan-Willem van de Meent, Lawson L. S. Wong, Thomas Kipf

CoRR, 2022

Factored World Models for Zero-Shot Generalization in Robotic Manipulation.

Ondrej Biza, Thomas Kipf, David Klee, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong

CoRR, 2022

Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning.

Peyman Bateni, Jarred Barber, Raghav Goyal, Vaden Masrani, Jan-Willem van de Meent, Leonid Sigal, Frank Wood

CoRR, 2022

Enhancing Few-Shot Image Classification with Unlabelled Examples.

Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Deriving Time-Averaged Active Inference from Control Principles.

Eli Sennesh, Jordan Theriault, Jan-Willem van de Meent, Lisa Feldman Barrett, Karen S. Quigley

Proceedings of the Active Inference - Third International Workshop, 2022

Learning Symmetric Embeddings for Equivariant World Models.

Jung Yeon Park, Ondrej Biza, Linfeng Zhao, Jan-Willem van de Meent, Robin Walters

Proceedings of the International Conference on Machine Learning, 2022

That's the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data.

Denis Jered McInerney, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Generator Surgery for Compressed Sensing.

Niklas Smedemark-Margulies, Jung Yeon Park, Max Daniels, Rose Yu, Jan-Willem van de Meent, Paul Hand

CoRR, 2021

Learning proposals for probabilistic programs with inference combinators.

Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem van de Meent

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Nested Variational Inference.

Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On the Impact of Random Seeds on the Fairness of Clinical Classifiers.

Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Conjugate Energy-Based Models.

Hao Wu, Babak Esmaeili, Michael L. Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent

Proceedings of the 38th International Conference on Machine Learning, 2021

Disentangling Representations of Text by Masking Transformers.

Xiongyi Zhang, Jan-Willem van de Meent, Byron C. Wallace

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Action Priors for Large Action Spaces in Robotics.

Ondrej Biza, Dian Wang, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

Rate-Regularization and Generalization in Variational Autoencoders.

Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Guiding Generative Graph Grammars of Dungeon Mission Graphs via Examples.

Abdelrahman Madkour, Stacy Marsella, Casper Harteveld, Magy Seif El-Nasr, Jan-Willem van de Meent

Proceedings of the Joint Proceedings of the AIIDE 2021 Workshops co-located with 17th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2021)(AAAI 2021), 2021

2020

Improving Few-Shot Visual Classification with Unlabelled Examples.

Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood

CoRR, 2020

Deep Markov Spatio-Temporal Factorization.

Amirreza Farnoosh, Behnaz Rezaei, Eli Zachary Sennesh, Zulqarnain Khan, Jennifer G. Dy, Ajay B. Satpute, J. Benjamin Hutchinson, Jan-Willem van de Meent, Sarah Ostadabbas

CoRR, 2020

Learning discrete state abstractions with deep variational inference.

Ondrej Biza, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong

CoRR, 2020

Neural Topographic Factor Analysis for fMRI Data.

Eli Sennesh, Zulqarnain Khan, Yiyu Wang, J. Benjamin Hutchinson, Ajay B. Satpute, Jennifer G. Dy, Jan-Willem van de Meent

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Query-Focused EHR Summarization to Aid Imaging Diagnosis.

Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace

Proceedings of the Machine Learning for Healthcare Conference, 2020

Amortized Population Gibbs Samplers with Neural Sufficient Statistics.

Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Evaluating Combinatorial Generalization in Variational Autoencoders.

Alican Bozkurt, Babak Esmaeili, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent

CoRR, 2019

Neural Topographic Factor Analysis for fMRI Data.

Eli Sennesh, Zulqarnain Khan, Jennifer G. Dy, Ajay B. Satpute, J. Benjamin Hutchinson, Jan-Willem van de Meent

CoRR, 2019

Structured Neural Topic Models for Reviews.

Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Structured Disentangled Representations.

Babak Esmaeili, Hao Wu, Sarthak Jain, Alican Bozkurt, N. Siddharth, Brooks Paige, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Can VAEs Generate Novel Examples?

Alican Bozkurt, Babak Esmaeili, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent

CoRR, 2018

Structured Representations for Reviews: Aspect-Based Variational Hidden Factor Models.

Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent

CoRR, 2018

Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs.

Iris Rubi Seaman, Jan-Willem van de Meent, David Wingate

CoRR, 2018

Composing Modeling and Inference Operations with Probabilistic Program Combinators.

Eli Sennesh, Adam Scibior, Hao Wu, Jan-Willem van de Meent

CoRR, 2018

On Exploration, Exploitation and Learning in Adaptive Importance Sampling.

Xiaoyu Lu, Tom Rainforth, Yuan Zhou, Jan-Willem van de Meent, Yee Whye Teh

CoRR, 2018

An Introduction to Probabilistic Programming.

Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood

CoRR, 2018

Hierarchical Disentangled Representations.

Babak Esmaeili, Hao Wu, Sarthak Jain, N. Siddharth, Brooks Paige, Jan-Willem van de Meent

CoRR, 2018

Learning Disentangled Representations of Texts with Application to Biomedical Abstracts.

Sarthak Jain, Edward Banner, Jan-Willem van de Meent, Iain James Marshall, Byron C. Wallace

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Learning Disentangled Representations with Semi-Supervised Deep Generative Models.

Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Inducing Interpretable Representations with Variational Autoencoders.

N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr

CoRR, 2016

Probabilistic structure discovery in time series data.

David Janz, Brooks Paige, Tom Rainforth, Jan-Willem van de Meent, Frank D. Wood

CoRR, 2016

Bayesian Optimization for Probabilistic Programs.

Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Design and Implementation of Probabilistic Programming Language Anglican.

David Tolpin, Jan-Willem van de Meent, Hongseok Yang, Frank D. Wood

Proceedings of the 28th Symposium on the Implementation and Application of Functional Programming Languages, 2016

Interacting Particle Markov Chain Monte Carlo.

Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood

Proceedings of the 33nd International Conference on Machine Learning, 2016

Black-Box Policy Search with Probabilistic Programs.

Jan-Willem van de Meent, Brooks Paige, David Tolpin, Frank D. Wood

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Adaptive Scheduling in MCMC and Probabilistic Programming.

David Tolpin, Jan-Willem van de Meent, Brooks Paige, Frank D. Wood

CoRR, 2015

Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data.

Max Greenfeld, Jan-Willem van de Meent, Dmitri S. Pavlichin, Hideo Mabuchi, Chris H. Wiggins, Ruben L. Gonzalez, Daniel Herschlag

BMC Bioinform., 2015

Probabilistic Programming in Anglican.

David Tolpin, Jan-Willem van de Meent, Frank D. Wood

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs.

David Tolpin, Jan-Willem van de Meent, Brooks Paige, Frank D. Wood

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Particle Gibbs with Ancestor Sampling for Probabilistic Programs.

Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

A New Approach to Probabilistic Programming Inference.

Frank D. Wood, Jan-Willem van de Meent, Vikash Mansinghka

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data.

Jan-Willem van de Meent, Jonathan E. Bronson, Frank D. Wood, Ruben L. Gonzalez, Chris Wiggins

Proceedings of the 30th International Conference on Machine Learning, 2013