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20242026
most citedLearning Neural Free-Energy Functionals with Pair-Correlation Matching

18 citations · 18 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

Purrception: Variational Flow Matching for Vector-Quantized Image Generation

Răzvan-Andrei Matişan, Vincent Tao Hu, Grigory Bartosh +6

We introduce Purrception, a variational flow matching approach for vector-quantized image generation that provides explicit categorical supervision while maintaining continuous tra…

cs.LG2025

Controlled Generation with Equivariant Variational Flow Matching

Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama +4

We derive a controlled generation objective within the framework of Variational Flow Matching (VFM), which casts flow matching as a variational inference problem. We demonstrate th…

cond-mat.soft2025

Learned Free-Energy Functionals from Pair-Correlation Matching for Dynamical Density Functional Theory

Karnik Ram, Jacobus Dijkman, René van Roij +4

Classical density functional theory (cDFT) and dynamical density functional theory (DDFT) are modern statistical mechanical theories for modeling many-body colloidal systems at the…

cs.LG2025

Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems

Maksim Zhdanov, Max Welling, Jan-Willem van de Meent

Large-scale physical systems defined on irregular grids pose significant scalability challenges for deep learning methods, especially in the presence of long-range interactions and…

cs.LG2025

Riemannian Variational Flow Matching for Material and Protein Design

Olga Zaghen, Floor Eijkelboom, Alison Pouplin +4

We present Riemannian Gaussian Variational Flow Matching (RG-VFM), a geometric extension of Variational Flow Matching (VFM) for generative modeling on manifolds. Motivated by the b…