Gradient Descent Quantizes ReLU Network Features. - Hartmut Maennel; Olivier Bousquet; Sylvain Gelly (CoRR, 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 001 (CoRR, 2018)

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 001; Gergely Neu (NeurIPS, 2019)

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 (NeurIPS, 2020)

Exact marginal inference in Latent Dirichlet Allocation. - Hartmut Maennel (CoRR, 2020)

Deep Learning Through the Lens of Example Difficulty. - Robert J. N. Baldock; Hartmut Maennel; Behnam Neyshabur (NeurIPS, 2021)

The Impact of Reinitialization on Generalization in Convolutional Neural Networks. - Ibrahim M. Alabdulmohsin; Hartmut Maennel; Daniel Keysers (CoRR, 2021)

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)

E3x: E(3)-Equivariant Deep Learning Made Easy. - Oliver T. Unke; Hartmut Maennel (CoRR, 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)

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 (Zenodo, 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 (Zenodo, 2025)