I am a PhD candidate in generative modeling at the University of Amsterdam, supervised by Jan-Willem van de Meent and Max Welling. My research explores flow matching, probabilistic inference, and creativity in deep learning. I developed Variational Flow Matching, a framework that unifies diffusion and flow models through variational inference. My goal is to create more creative models, with the goal of developing models that go beyond realism, capable of conceptually grounded, semantically rich, and imaginative generation.
PhD in Artificial Intelligence
University of Amsterdam
MSc in Artificial Intelligence (Cum Laude)
University of Amsterdam
BSc in Artificial Intelligence (Cum Laude)
Utrecht University
Purrception: Variational Flow Matching for Vector-Quantized Image Generation
Răzvan-Andrei Matişan, Vincent Tao Hu, Grigory Bartosh, Björn Ommer, Cees GM Snoek, Max Welling, Jan-Willem van de Meent, Mohammad Mahdi Derakhshani*, Floor Eijkelboom*
arXiv preprint
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
arXiv preprint
Discovering Lie Groups with Flow Matching
Jung Yeon Park, Yuxuan Chen, Floor Eijkelboom, Jan-Willem van de Meent, Lawson L.S. Wong, Robin Walters
Under review
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
Exponential Family Variational Flow Matching for Tabular Data Generation
Andrés Guzmán-Cordero*, Floor Eijkelboom*, Jan-Willem van de Meent
ICML 2025
Towards Variational Flow Matching on General Geometries
Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Erik J Bekkers
ICLR 2025 Workshop on Deep Generative Model in Machine Learning (Best Paper award)
Variational Flow Matching for Graph Generation
Floor Eijkelboom*, Grigory Bartosh*, Christian A. Naesseth, Max Welling, Jan-Willem van de Meent
NeurIPS 2024
Clifford Group Equivariant Simplicial Message Passing Networks
Cong Liu*, David Ruhe*, Floor Eijkelboom, Patrick Forré
ICLR 2024
E(n) Equivariant Message Passing Simplicial Networks
Floor Eijkelboom, Rob Hesselink, Erik J Bekkers
ICML 2024