Floor Eijkelboom 🐋

Floor Eijkelboom

PhD Candidate Generative AI

University of Amsterdam

Professional Summary

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.

Education

PhD in Artificial Intelligence

University of Amsterdam

MSc in Artificial Intelligence (Cum Laude)

University of Amsterdam

BSc in Artificial Intelligence (Cum Laude)

Utrecht University

Interests

Generative AI Creativity Physics-Inspired ML Probabilistic Inference Philosophy

Preprint

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

Published

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