214 citations
- Asahi Kasei (Japan)JP3 papers
- New York UniversityUS3 papers
- Memorial Sloan Kettering Cancer CenterUS2 papers
- Open Molecular Software Foundation2 papers
- Tri-Institutional PhD Program in Chemical BiologyUS2 papers
- University of California, BerkeleyUS2 papers
- University of WashingtonUS2 papers
- Argonne National LaboratoryUS1 paper
- Beijing Children’s HospitalCN1 paper
- Beijing Obstetrics and Gynecology HospitalCN1 paper
- Biogen (Belgium)BE1 paper
- Capital Medical UniversityCN1 paper
8 papers
On the design space between molecular mechanics and machine learning force fields
Yuanqing Wang, Kenichiro Takaba, Michael S. Chen +14
A force field as accurate as quantum mechanics (QM) and as fast as molecular mechanics (MM), with which one can simulate a biomolecular system efficiently enough and meaningfully e…
Discovering Effective Policies for Land-Use Planning with Neuroevolution
Daniel Young, Olivier Francon, Elliot Meyerson +5
How areas of land are allocated for different uses, such as forests, urban areas, and agriculture, has a large effect on the terrestrial carbon balance, and therefore climate chang…
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali +50
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To…
Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond
Kenichiro Takaba, Iván Pulido, Pavan Kumar Behara +11
The development of reliable and extensible molecular mechanics (MM) force fields -- fast, empirical models characterizing the potential energy surface of molecular systems -- is in…
EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment
Yuanqing Wang, Iván Pulido, Kenichiro Takaba +4
Atomic partial charges are crucial parameters in molecular dynamics (MD) simulation, dictating the electrostatic contributions to intermolecular energies, and thereby the potential…
Meta-brain Models: biologically-inspired cognitive agents
Bradly Alicea, Jesse Parent
Artificial Intelligence (AI) systems based solely on neural networks or symbolic computation present a representational complexity challenge. While minimal representations can prod…