KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory

no code implementations • 8 May 2023 • Roman Remme, Tobias Kaczun, Maximilian Scheurer, Andreas Dreuw, Fred A. Hamprecht

We here set out to learn the kinetic energy functional from ground truth provided by the more expensive Kohn-Sham density functional theory.

Learning the Arrow of Time for Problems in Reinforcement Learning

no code implementations • ICLR 2020 • Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio

We humans have an innate understanding of the asymmetric progression of time, which we use to efficiently and safely perceive and manipulate our environment.

reinforcement-learning Reinforcement Learning (RL)

Learning the Arrow of Time

no code implementations • 2 Jul 2019 • Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio

We humans seem to have an innate understanding of the asymmetric progression of time, which we use to efficiently and safely perceive and manipulate our environment.