868 citations · 9.4k across the 68 of their papers we have counts for
7 papers · 1 filter
Curiosity in exploring chemical space: Intrinsic rewards for deep molecular reinforcement learning
Luca A. Thiede, Mario Krenn, AkshatKumar Nigam +1
Computer-aided design of molecules has the potential to disrupt the field of drug and material discovery. Machine learning, and deep learning, in particular, have been topics where…
Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations
Cynthia Shen, Mario Krenn, Sagi Eppel +1
Computer-based de-novo design of functional molecules is one of the most prominent challenges in cheminformatics today. As a result, generative and evolutionary inverse designs fro…
Scientific intuition inspired by machine learning generated hypotheses
Pascal Friederich, Mario Krenn, Isaac Tamblyn +1
Machine learning with application to questions in the physical sciences has become a widely used tool, successfully applied to classification, regression and optimization tasks in…
Quantum Computer-Aided design of Quantum Optics Hardware
Jakob S. Kottmann, Mario Krenn, Thi Ha Kyaw +2
The parameters of a quantum system grow exponentially with the number of involved quantum particles. Hence, the associated memory requirement goes well beyond the limit of best cla…
Conceptual understanding through efficient inverse-design of quantum optical experiments
Mario Krenn, Jakob Kottmann, Nora Tischler +1
One crucial question within artificial intelligence research is how this technology can be used to discover new scientific concepts and ideas. We present Theseus, an explainable AI…
Quantum Experiments and Hypergraphs: Multi-Photon Sources for Quantum Interference, Quantum Computation and Quantum Entanglement
Xuemei Gu, Lijun Chen, Mario Krenn
We introduce the concept of hypergraphs to describe quantum optical experiments with probabilistic multi-photon sources. Every hyperedge represents a correlated photon source, and…