Frank Hellmann

Researcher, Potsdam Institute for Climate Impact Research

Joined

March 2022

Names

Frank Hellmann (Preferred)

Emails

****@pik-potsdam.de (Confirmed)

Personal Links

ORCID

Career & Education History

Researcher

Potsdam Institute for Climate Impact Research (pik-potsdam.de)

2014 – Present

Advisors, Relations & Conflicts

Coauthor

Christian Nauck

Present

Postdoc Advisor

Juergen Kurths

Present

Coauthor

Michael Lindner

Present

Coworker

Maximilian Gelbrecht

Present

Coworker

Niklas Boers

Present

Coworker

Alistair White

Present

Coauthor

Konstantin Schürholt

Present

Coworker

Antonia S J S Mey

Present

Coworker

Junyou Zhu

Present

Expertise

No areas of expertise listed

Publications

Learning Dynamic Stability Landscapes from Graph Topology
Christian Nauck, Junyou Zhu, Michael Lindner, Frank Hellmann
- Submitted to ICLR 2026
- Readers: Everyone
SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning
Junyou Zhu, Langzhou He, Chao Gao, Dongpeng Hou, Zhen Su, Philip S. Yu, Juergen Kurths, Frank Hellmann
- ICML 2025 poster
- Readers: Everyone
Projected Neural Differential Equations for Learning Constrained Dynamics
Alistair White, Anna Büttner, Maximilian Gelbrecht, Valentin Duruisseaux, Niki Kilbertus, Frank Hellmann, Niklas Boers
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Projected Neural Differential Equations for Power Grid Modeling with Constraints
Alistair White, Anna Büttner, Maximilian Gelbrecht, Niki Kilbertus, Frank Hellmann, Niklas Boers
- D3S3 2024 Poster
- Readers: Everyone
Dirac--Bianconi Graph Neural Networks - Enabling long-range graph predictions
Christian Nauck, Rohan Gorantla, Michael Lindner, Konstantin Schürholt, Antonia S J S Mey, Frank Hellmann
- ICML 2024 Workshop GRaM
- Readers: Everyone
Deep Graph Predictions using Dirac-Bianconi Graph Neural Networks
Christian Nauck, Rohan Gorantla, Michael Lindner, Konstantin Schürholt, Antonia S J S Mey, Frank Hellmann
- Submitted to ICLR 2024
- Readers: Everyone
Towards predicting dynamic stability of power grids with Graph Neural Networks
Christian Nauck, Michael Lindner, Konstantin Schürholt, Frank Hellmann
- Published: 01 Feb 2023, Last Modified: 13 Feb 2023
- Submitted to ICLR 2023
- Readers: Everyone

Frank Hellmann

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Learning Dynamic Stability Landscapes from Graph Topology

SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning

Projected Neural Differential Equations for Learning Constrained Dynamics

Projected Neural Differential Equations for Power Grid Modeling with Constraints

Dirac--Bianconi Graph Neural Networks - Enabling long-range graph predictions

Deep Graph Predictions using Dirac-Bianconi Graph Neural Networks

Towards predicting dynamic stability of power grids with Graph Neural Networks

Co-Authors