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• Towards Exact Molecular Dynamics Simulations with Machine-Learned Force Fields
  2018 · 673 citations
• SchNet: A continuous-filter convolutional neural network for modeling quantum interactions
  2017 · 470 citations
• Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields
  2022 · 14 citations
• Accurate global machine learning force fields for molecules with hundreds of atoms
  2022 · 9 citations
• Euclidean Fast Attention -- Machine Learning Global Atomic Representations at Linear Cost
  2024 · 2 citations
• Sampling 3D Molecular Conformers with Diffusion Transformers
  2025 · 1 citations
• Towards Linearly Scaling and Chemically Accurate Global Machine Learning Force Fields for Large Molecules
  2022 · 1 citations
• BIGDML: Towards Exact Machine Learning Force Fields for Materials
  2021 · 1 citations
• From Peptides to Nanostructures: A Euclidean Transformer for Fast and Stable Machine Learned Force Fields
  2023 · 1 citations
• How Atoms Interact Within Molecules
  2026
• Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
  2026
• Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence
  2022