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Jan-Willem van de Meent
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2020 – today
- 2022
- [c24]Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood:
Enhancing Few-Shot Image Classification with Unlabelled Examples. WACV 2022: 1597-1606 - [i35]Peyman Bateni, Jarred Barber, Raghav Goyal, Vaden Masrani, Jan-Willem van de Meent, Leonid Sigal, Frank Wood:
Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning. CoRR abs/2201.05151 (2022) - [i34]Ondrej Biza, Thomas Kipf, David Klee, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong:
Factored World Models for Zero-Shot Generalization in Robotic Manipulation. CoRR abs/2202.05333 (2022) - [i33]Jung Yeon Park, Ondrej Biza, Linfeng Zhao, Jan-Willem van de Meent, Robin Walters:
Learning Symmetric Embeddings for Equivariant World Models. CoRR abs/2204.11371 (2022) - [i32]Ondrej Biza, Robert Platt, Jan-Willem van de Meent, Lawson L. S. Wong, Thomas Kipf:
Binding Actions to Objects in World Models. CoRR abs/2204.13022 (2022) - 2021
- [c23]Alican Bozkurt, Babak Esmaeili, Jean-Baptiste Tristan, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent:
Rate-Regularization and Generalization in Variational Autoencoders. AISTATS 2021: 3880-3888 - [c22]Ondrej Biza, Dian Wang, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong:
Action Priors for Large Action Spaces in Robotics. AAMAS 2021: 205-213 - [c21]Xiongyi Zhang, Jan-Willem van de Meent, Byron C. Wallace:
Disentangling Representations of Text by Masking Transformers. EMNLP (1) 2021: 778-791 - [c20]Hao Wu, Babak Esmaeili
, Michael L. Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent:
Conjugate Energy-Based Models. ICML 2021: 11228-11239 - [c19]Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace:
On the Impact of Random Seeds on the Fairness of Clinical Classifiers. NAACL-HLT 2021: 3808-3823 - [c18]Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent:
Nested Variational Inference. NeurIPS 2021: 20423-20435 - [c17]Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem van de Meent:
Learning proposals for probabilistic programs with inference combinators. UAI 2021: 1056-1066 - [i31]Ondrej Biza, Dian Wang, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong:
Action Priors for Large Action Spaces in Robotics. CoRR abs/2101.04178 (2021) - [i30]Niklas Smedemark-Margulies, Jung Yeon Park, Max Daniels, Rose Yu, Jan-Willem van de Meent, Paul Hand:
Generator Surgery for Compressed Sensing. CoRR abs/2102.11163 (2021) - [i29]Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem van de Meent:
Learning Proposals for Probabilistic Programs with Inference Combinators. CoRR abs/2103.00668 (2021) - [i28]Silvio Amir, Jan-Willem van de Meent, Byron C. Wallace:
On the Impact of Random Seeds on the Fairness of Clinical Classifiers. CoRR abs/2104.06338 (2021) - [i27]Xiongyi Zhang, Jan-Willem van de Meent, Byron C. Wallace:
Disentangling Representations of Text by Masking Transformers. CoRR abs/2104.07155 (2021) - [i26]Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent:
Nested Variational Inference. CoRR abs/2106.11302 (2021) - [i25]Hao Wu, Babak Esmaeili, Michael L. Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent:
Conjugate Energy-Based Models. CoRR abs/2106.13798 (2021) - 2020
- [c16]Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent:
Amortized Population Gibbs Samplers with Neural Sufficient Statistics. ICML 2020: 10421-10431 - [c15]Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
Query-Focused EHR Summarization to Aid Imaging Diagnosis. MLHC 2020: 632-659 - [c14]Eli Sennesh, Zulqarnain Khan, Yiyu Wang, J. Benjamin Hutchinson, Ajay B. Satpute, Jennifer G. Dy, Jan-Willem van de Meent:
Neural Topographic Factor Analysis for fMRI Data. NeurIPS 2020 - [i24]Ondrej Biza, Robert Platt Jr., Jan-Willem van de Meent, Lawson L. S. Wong:
Learning discrete state abstractions with deep variational inference. CoRR abs/2003.04300 (2020) - [i23]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:
Deep Markov Spatio-Temporal Factorization. CoRR abs/2003.09779 (2020) - [i22]Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace:
Query-Focused EHR Summarization to Aid Imaging Diagnosis. CoRR abs/2004.04645 (2020) - [i21]Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood:
Improving Few-Shot Visual Classification with Unlabelled Examples. CoRR abs/2006.12245 (2020)
2010 – 2019
- 2019
- [c13]Babak Esmaeili, Hao Wu, Sarthak Jain, Alican Bozkurt, N. Siddharth, Brooks Paige, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent:
Structured Disentangled Representations. AISTATS 2019: 2525-2534 - [c12]Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent:
Structured Neural Topic Models for Reviews. AISTATS 2019: 3429-3439 - [i20]Eli Sennesh, Zulqarnain Khan, Jennifer G. Dy, Ajay B. Satpute, J. Benjamin Hutchinson, Jan-Willem van de Meent:
Neural Topographic Factor Analysis for fMRI Data. CoRR abs/1906.08901 (2019) - [i19]Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent:
Amortized Population Gibbs Samplers with Neural Sufficient Statistics. CoRR abs/1911.01382 (2019) - [i18]Alican Bozkurt, Babak Esmaeili, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent:
Evaluating Combinatorial Generalization in Variational Autoencoders. CoRR abs/1911.04594 (2019) - 2018
- [c11]Sarthak Jain, Edward Banner, Jan-Willem van de Meent, Iain James Marshall, Byron C. Wallace:
Learning Disentangled Representations of Texts with Application to Biomedical Abstracts. EMNLP 2018: 4683-4693 - [i17]Babak Esmaeili, Hao Wu, Sarthak Jain, N. Siddharth, Brooks Paige, Jan-Willem van de Meent:
Hierarchical Disentangled Representations. CoRR abs/1804.02086 (2018) - [i16]Sarthak Jain, Edward Banner, Jan-Willem van de Meent, Iain James Marshall, Byron C. Wallace:
Learning Disentangled Representations of Texts with Application to Biomedical Abstracts. CoRR abs/1804.07212 (2018) - [i15]Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood:
An Introduction to Probabilistic Programming. CoRR abs/1809.10756 (2018) - [i14]Xiaoyu Lu, Tom Rainforth, Yuan Zhou, Jan-Willem van de Meent, Yee Whye Teh:
On Exploration, Exploitation and Learning in Adaptive Importance Sampling. CoRR abs/1810.13296 (2018) - [i13]Eli Sennesh, Adam Scibior, Hao Wu, Jan-Willem van de Meent:
Composing Modeling and Inference Operations with Probabilistic Program Combinators. CoRR abs/1811.05965 (2018) - [i12]Iris Rubi Seaman, Jan-Willem van de Meent, David Wingate:
Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs. CoRR abs/1812.01569 (2018) - [i11]Babak Esmaeili, Hongyi Huang, Byron C. Wallace, Jan-Willem van de Meent:
Structured Representations for Reviews: Aspect-Based Variational Hidden Factor Models. CoRR abs/1812.05035 (2018) - [i10]Alican Bozkurt, Babak Esmaeili, Dana H. Brooks, Jennifer G. Dy, Jan-Willem van de Meent:
Can VAEs Generate Novel Examples? CoRR abs/1812.09624 (2018) - 2017
- [c10]Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr:
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. NIPS 2017: 5925-5935 - [i9]N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr:
Learning Disentangled Representations with Semi-Supervised Deep Generative Models. CoRR abs/1706.00400 (2017) - [i8]Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood:
Bayesian Optimization for Probabilistic Programs. CoRR abs/1707.04314 (2017) - 2016
- [c9]Jan-Willem van de Meent, Brooks Paige, David Tolpin, Frank D. Wood:
Black-Box Policy Search with Probabilistic Programs. AISTATS 2016: 1195-1204 - [c8]Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood:
Interacting Particle Markov Chain Monte Carlo. ICML 2016: 2616-2625 - [c7]David Tolpin
, Jan-Willem van de Meent, Hongseok Yang, Frank D. Wood:
Design and Implementation of Probabilistic Programming Language Anglican. IFL 2016: 6:1-6:12 - [c6]Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood:
Bayesian Optimization for Probabilistic Programs. NIPS 2016: 280-288 - [i7]David Tolpin, Jan-Willem van de Meent, Hongseok Yang, Frank D. Wood:
Design and Implementation of Probabilistic Programming Language Anglican. CoRR abs/1608.05263 (2016) - [i6]David Janz, Brooks Paige, Tom Rainforth, Jan-Willem van de Meent, Frank D. Wood:
Probabilistic structure discovery in time series data. CoRR abs/1611.06863 (2016) - [i5]N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr:
Inducing Interpretable Representations with Variational Autoencoders. CoRR abs/1611.07492 (2016) - 2015
- [j1]Max Greenfeld, Jan-Willem van de Meent, Dmitri S. Pavlichin, Hideo Mabuchi, Chris H. Wiggins, Ruben L. Gonzalez, Daniel Herschlag:
Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data. BMC Bioinform. 16: 3:1-3:4 (2015) - [c5]Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood:
Particle Gibbs with Ancestor Sampling for Probabilistic Programs. AISTATS 2015 - [c4]David Tolpin
, Jan-Willem van de Meent, Frank D. Wood:
Probabilistic Programming in Anglican. ECML/PKDD (3) 2015: 308-311 - [c3]David Tolpin
, Jan-Willem van de Meent, Brooks Paige, Frank D. Wood:
Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs. ECML/PKDD (2) 2015: 311-326 - [i4]David Tolpin, Jan-Willem van de Meent, Brooks Paige, Frank D. Wood:
Adaptive Scheduling in MCMC and Probabilistic Programming. CoRR abs/1501.05677 (2015) - [i3]Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood:
Particle Gibbs with Ancestor Sampling for Probabilistic Programs. CoRR abs/1501.06769 (2015) - [i2]Frank D. Wood, Jan-Willem van de Meent, Vikash Mansinghka:
A New Approach to Probabilistic Programming Inference. CoRR abs/1507.00996 (2015) - [i1]Jan-Willem van de Meent, David Tolpin, Brooks Paige, Frank D. Wood:
Black-Box Policy Search with Probabilistic Programs. CoRR abs/1507.04635 (2015) - 2014
- [c2]Frank D. Wood, Jan-Willem van de Meent, Vikash Mansinghka:
A New Approach to Probabilistic Programming Inference. AISTATS 2014: 1024-1032 - 2013
- [c1]Jan-Willem van de Meent, Jonathan E. Bronson, Frank D. Wood, Ruben L. Gonzalez, Chris Wiggins:
Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data. ICML (2) 2013: 361-369
Coauthor Index
aka: Frank Wood

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last updated on 2022-05-04 23:16 CEST by the dblp team
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