Daniel Pelt — accepted AI-conference papers

2026

DM4CT: Benchmarking Diffusion Models for Computed Tomography Reconstruction

Jiayang Shi, Daniel Pelt, Joost Batenburg

ICLR 2026poster

Diffusion models have recently emerged as powerful priors for solving inverse problems. While computed tomography (CT) is theoretically a linear inverse problem, it poses many practical challenges. These include correlated noise, artifact structures, reliance on system geometry, and misaligned value…

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2025

Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces

Alejandro García-Castellanos, David Wessels, Nicky J. van den Berg, Remco Duits, Daniel Pelt, Erik J Bekkers

NeurIPS 2025poster

We introduce Equivariant Neural Eikonal Solvers, a novel framework that integrates Equivariant Neural Fields (ENFs) with Neural Eikonal Solvers. Our approach employs a single neural field where a unified shared backbone is conditioned on signal-specific latent variables – represented as point clouds…

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