See my complete publications on Google Scholar.

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2026

Riemannian Archetypal Analysis: Interpretable Non-linear Data Analysis on Deformed Star Distributions.

Willem Diepeveen, Deanna Needell

Preprint 2026

[Paper] [Code]

Data-driven geometry Representation learning Manifold optimization
Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data

Willem Diepeveen, Oscar Leong

Preprint 2026

[Paper] [Code]

Data-driven geometry Manifold optimization
Latent Diffeomorphic Dynamic Mode Decomposition

Willem Diepeveen, Jon Schwenk, Andrea L. Bertozzi

Applied Mathematics Letters 2026

[Paper] [Code]

Applications

2025

Curvature Corrected Tangent Space-based Approximation of Manifold-valued Data

Willem Diepeveen, Joyce Chew, Deanna Needell

Information and Inference: A Journal of the IMA 2025

[Paper] [Code]

Representation learning
Iso-Riemannian Optimization on Learned Data Manifolds

Willem Diepeveen, Melanie Weber

Preprint 2025

[Paper] [Code]

Manifold optimization
Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows

Willem Diepeveen*, Georgios Batzolis*, Zakhar Shumaylov, Carola-Bibiane Schonlieb (* equal contribution)

ICML 2025

[Paper] [Code]

Data-driven geometry Representation learning
Pullback Flow Matching on Data Manifolds

Friso de Kruiff, Erik J Bekkers, Ozan Oktem, Carola-Bibiane Schonlieb, Willem Diepeveen

ICML Generative AI and Biology (GenBio) Workshop 2025

[Paper]

Applications
Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian Geometry

Willem Diepeveen, Deanna Needell

Preprint 2025

[Paper] [Code]

Data-driven geometry Representation learning
Direct Atomistic Reconstruction in Homogeneous Cryo-EM Using Protein Geometry Regularization

Jonathan Krook, Willem Diepeveen, Ozan Oktem

SSVM 2025 2025

[Paper]

Applications
Curvature Corrected Nonnegative Manifold Data Factorization

Joyce Chew, Willem Diepeveen, Deanna Needell

Preprint 2025

[Paper]

Representation learning

2024

Pulling Back Symmetric Riemannian Geometry for Data Analysis

Willem Diepeveen

Preprint 2024

[Paper] [Code]

Data-driven geometry Representation learning Manifold optimization
Riemannian Geometry for Efficient Analysis of Protein Dynamics Data

Willem Diepeveen, Carlos Esteve-Yague, Jan Lellmann, Ozan Oktem, Carola-Bibiane Schonlieb

Proceedings of the National Academy of Sciences 2024

[Paper] [Code]

Data-driven geometry Applications
Physics-informed Geometric Regularization of Heterogeneous Reconstructions in Cryo-EM

Victor Prins, Willem Diepeveen, Erik J Bekkers, Ozan Oktem

ICLR Workshop on Generative and Experimental Perspectives for Biomolecular Design 2024

[Paper]

Applications

2023

Regularizing Orientation Estimation in Cryogenic Electron Microscopy: Three-Dimensional Map Refinement through Measure-Based Lifting over Riemannian Manifolds

Willem Diepeveen, Jan Lellmann, Ozan Oktem, Carola-Bibiane Schonlieb

SIAM Journal on Imaging Sciences 2023

[Paper] [Code]

Manifold optimization Applications
Spectral Decomposition of Atomic Structures in Heterogeneous Cryo-EM

Carlos Esteve-Yague, Willem Diepeveen, Ozan Oktem, Carola-Bibiane Schonlieb

Inverse Problems 2023

[Paper]

Applications

2021

An Inexact Semismooth Newton Method on Riemannian Manifolds with Application to Duality-Based Total Variation Denoising

Willem Diepeveen, Jan Lellmann

SIAM Journal on Imaging Sciences 2021

[Paper] [Code]

Manifold optimization