3 papers
cs.CV2026
Platonic Transformers: A Solid Choice For Equivariance
Mohammad Mohaiminul Islam, Rishabh Anand, David R. Wessels +7
While widespread, Transformers lack inductive biases for geometric symmetries common in science and computer vision. Existing equivariant methods often sacrifice the efficiency and…
stat.ML2026
Flowing with Confidence
Friso de Kruiff, Dario Coscia, Max Welling +1
Generative models can produce nonsensical text, unrealistic images, and unstable materials faster than simulation or human review can absorb; without per-sample confidence, trust e…
cs.LG2025
Pullback Flow Matching on Data Manifolds
Friso de Kruiff, Erik Bekkers, Ozan Ãktem +2
We propose Pullback Flow Matching (PFM), a novel framework for generative modeling on data manifolds. Unlike existing methods that assume or learn restrictive closed-form manifold…