Jan-Willem van de Meent
26 papers · 2016–2025 · 9 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (9) πΊοΈ Taxonomy Completionist (10) π§ Keyword Pioneer π Interdisciplinary Bridge π Academic Marathon (9)
π
Academic Marathon
(9)
π
Cross-Pollinator
(6)
π
Renaissance Researcher
(8)
π§¬
Topic Evolution
ποΈ
Keyword Collector
(114)
π
Century Club
(26)
β‘
Prolific Year
(6)
π₯
Unstoppable
(10)
Conferences
NIPS (8)
ICML (6)
EMNLP (4)
AISTATS (2)
NAACL (2)
CORL (1)
ICLR (1)
UAI (1)
WACV (1)
Top co-authors
Research topics
Keywords
variational inference
(6)
variational autoencoder
(4)
electronic health record
(4)
importance sampling
(3)
disentangled representation
(3)
representation learning
(3)
unsupervised learning
(2)
large language model
(2)
generative model
(2)
amortized inference
(2)
robotic manipulation
(1)
kl divergence
(1)
topic modeling
(1)
bert model
(1)
medical imaging
(1)
approximate inference
(1)
embedding space
(1)
computational efficiency
(1)
feature extraction
(1)
feature learning
(1)
Papers
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
ICML 2025
Exponential Family Variational Flow Matching for Tabular Data Generation
ICML 2025
Controlled Generation with Equivariant Variational Flow Matching
ICML 2025
Practical Shuffle Coding
NIPS 2024
VISA: Variational Inference with Sequential Sample-Average Approximations
NIPS 2024
Entropy Coding of Unordered Data Structures
ICLR 2024
Towards Reducing Diagnostic Errors with Interpretable Risk Prediction
NAACL 2024
Variational Flow Matching for Graph Generation
NIPS 2024
One-shot Imitation Learning via Interaction Warping
CORL 2023
Topological Obstructions and How to Avoid Them
NIPS 2023
CHiLL: Zero-shot Custom Interpretable Feature Extraction from Clinical Notes with Large Language Models
EMNLP 2023
Enhancing Few-Shot Image Classification With Unlabelled Examples
WACV 2022
Thatβs the Wrong Lung! Evaluating and Improving the Interpretability of Unsupervised Multimodal Encoders for Medical Data
EMNLP 2022
Learning Symmetric Embeddings for Equivariant World Models
ICML 2022
Learning proposals for probabilistic programs with inference combinators
UAI 2021
Rate-Regularization and Generalization in Variational Autoencoders
AISTATS 2021
Conjugate Energy-Based Models
ICML 2021
Nested Variational Inference
NIPS 2021
On the Impact of Random Seeds on the Fairness of Clinical Classifiers
NAACL 2021
Disentangling Representations of Text by Masking Transformers
EMNLP 2021
Neural Topographic Factor Analysis for fMRI Data
NIPS 2020
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
ICML 2020
Structured Neural Topic Models for Reviews
AISTATS 2019
Learning Disentangled Representations of Texts with Application to Biomedical Abstracts
EMNLP 2018
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
NIPS 2017
Bayesian Optimization for Probabilistic Programs
NIPS 2016