Hartmut Maennel

According to our database, Hartmut Maennel authored at least 13 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

AI co-mathematician: Accelerating mathematicians with agentic AI.

Daniel Zheng, Ingrid von Glehn, Yori Zwols, Iuliya Beloshapka, Lars Buesing, Daniel M. Roy, Martin Wattenberg, Bogdan Georgiev, Tatiana Schmidt, Andrew Cowie, Fernanda B. Viégas, Dimitri Kanevsky, Vineet Kahlon, Hartmut Maennel, Sophia Alj, George Holland, Alex Davies, Pushmeet Kohli

CoRR, May, 2026

2025

Data from: The QCML dataset, Quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations.

Stefan Ganscha, Oliver T. Unke, Daniel Ahlin, Hartmut Maennel, Sergii Kashubin, Klaus-Robert Müller

Dataset, 2025

Data from: The QCML dataset, Quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations.

Stefan Ganscha, Oliver T. Unke, Daniel Ahlin, Hartmut Maennel, Sergii Kashubin, Klaus-Robert Müller

Dataset, 2025

2024

Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties.

Hartmut Maennel, Oliver T. Unke, Klaus-Robert Müller

CoRR, 2024

E3x: E(3)-Equivariant Deep Learning Made Easy.

Oliver T. Unke, Hartmut Maennel

CoRR, 2024

2022

Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations.

Oliver T. Unke, Martin Stöhr, Stefan Ganscha, Thomas Unterthiner, Hartmut Maennel, Sergii Kashubin, Daniel Ahlin, Michael Gastegger, Leonardo Medrano Sandonas, Alexandre Tkatchenko, Klaus-Robert Müller

CoRR, 2022

2021

The Impact of Reinitialization on Generalization in Convolutional Neural Networks.

Ibrahim M. Alabdulmohsin, Hartmut Maennel, Daniel Keysers

CoRR, 2021

Deep Learning Through the Lens of Example Difficulty.

Robert J. N. Baldock, Hartmut Maennel, Behnam Neyshabur

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Exact marginal inference in Latent Dirichlet Allocation.

Hartmut Maennel

CoRR, 2020

What Do Neural Networks Learn When Trained With Random Labels?

Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates.

Carlos Riquelme, Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto, Gergely Neu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem.

Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto

CoRR, 2018

Gradient Descent Quantizes ReLU Network Features.

Hartmut Maennel, Olivier Bousquet, Sylvain Gelly

CoRR, 2018