292 citations · 409 across the 5 of their papers we have counts for
5 papers
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang, Limei Wang, Jacob Helwig +60
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
Mario Krenn, Lorenzo Buffoni, Bruno Coutinho +13
A tool that could suggest new personalized research directions and ideas by taking insights from the scientific literature could significantly accelerate the progress of science. A…
LIMO: Latent Inceptionism for Targeted Molecule Generation
Peter Eckmann, Kunyang Sun, Bo Zhao +3
Generation of drug-like molecules with high binding affinity to target proteins remains a difficult and resource-intensive task in drug discovery. Existing approaches primarily emp…
SELFIES and the future of molecular string representations
Mario Krenn, Qianxiang Ai, Senja Barthel +28
Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include…
Deep Bayesian Active Learning for Accelerating Stochastic Simulation
Dongxia Wu, Ruijia Niu, Matteo Chinazzi +3
Stochastic simulations such as large-scale, spatiotemporal, age-structured epidemic models are computationally expensive at fine-grained resolution. While deep surrogate models can…