3 citations · 8 across the 10 of their papers we have counts for
17 papers
Pawsterior: Variational Flow Matching for Structured Simulation-Based Inference
Jorge Carrasco-Pollo, Floor Eijkelboom, Jan-Willem van de Meent
We introduce Pawsterior, a variational flow-matching framework for improved and extended simulation-based inference (SBI). Many SBI problems involve posteriors constrained by struc…
CORDS: Continuous Representations of Discrete Structures
Tin Hadži Veljković, Erik Bekkers, Michael Tiemann +1
Many learning problems require predicting sets of objects when the number of objects is not known beforehand. Examples include object detection, molecular modeling, and scientific…
MSPT: Efficient Large-Scale Physical Modeling via Parallelized Multi-Scale Attention
Pedro M. P. Curvo, Jan-Willem van de Meent, Maksim Zhdanov
A key scalability challenge in neural solvers for industrial-scale physics simulations is efficiently capturing both fine-grained local interactions and long-range global dependenc…
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…
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…
Exponential Family Variational Flow Matching for Tabular Data Generation
Andrés Guzmán-Cordero, Floor Eijkelboom, Jan-Willem van de Meent
While denoising diffusion and flow matching have driven major advances in generative modeling, their application to tabular data remains limited, despite its ubiquity in real-world…