1.9k citations
- Robert Bosch (United States)US15 papers
- Harvard UniversityUS4 papers
- Carnegie Mellon UniversityUS3 papers
- The University of Texas at AustinUS3 papers
- University of MichiganUS3 papers
- Argonne National LaboratoryUS2 papers
- École Polytechnique Fédérale de LausanneCH2 papers
- Lawrence Berkeley National LaboratoryUS2 papers
- Robert Bosch (Germany)DE2 papers
- Tech-X Corporation (United States)US2 papers
- University of California, Los AngelesUS2 papers
- University of ChicagoUS2 papers
16 papers
CoopReflect: Towards Natural Language Communication for Cooperative Autonomous Driving via Multi-Agent Learning
Jiaxun Cui, Chen Tang, Jarrett Holtz +4
Past work has demonstrated that autonomous vehicles can drive more safely if they communicate with each other. However, this communication is usually not human-understandable. Usin…
Room-temperature decomposition of the ethaline deep eutectic solvent
Julia H. Yang, Amanda Whai Shin Ooi, Zachary A. H. Goodwin +5
Environmentally-benign, non-toxic electrolytes with combinatorial design spaces are excellent candidates for green solvents, green leaching agents, and carbon capture sources. Here…
OnionVQE Optimization Strategy for Ground State Preparation on NISQ Devices
Katerina Gratsea, Johannes Selisko, Maximilian Amsler +3
The Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ)…
Nonlocal Machine-Learned Exchange Functional for Molecules and Solids
Kyle Bystrom, Boris Kozinsky
The design of better exchange-correlation functionals for Density Functional Theory (DFT) is a central challenge of modern electronic structure theory. However, current development…
OPTIMADE, an API for exchanging materials data
Casper W. Andersen, Rickard Armiento, Evgeny Blokhin +53
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible an…
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials
Simon Batzner, Albert Musaelian, Lixin Sun +6
This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio calculations f…