Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: learning atoms for materials discovery .
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
A computational challenge problem in materials discovery: synthetic problem generator and real-world datasets
Crystal Structure Prediction via Deep Learning.
N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials
MoleculeNet : A Benchmark for Molecular Machine Learning
Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics
A predictive machine learning approach for microstructure optimization and materials design
Deep Learning for Computational Chemistry
Automatically Extracting Action Graphs from Materials Science Synthesis Procedures
Learning to Predict Chemical Reactions
Material recognition in the wild with the Materials in Context Database
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
smt - aided combinatorial materials discovery .
Convolutional Embedding of Attributed Molecular Graphs for Physical Property Prediction.
Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
Direct Synthesis of van der Waals Solids
Neural Message Passing for Quantum Chemistry
Electronic structure calculations with GPAW: A real-space implementation of the projector augmented-wave method
Semi-supervised learning of hierarchical representations of molecules using neural message passing
Scalable Quantum Simulation of Molecular Energies
learning representations by back - propagating errors .
A Q-band (40–45 GHz) 16-element phased-array transmitter in 0.18-μm SiGe BiCMOS technology
Algorithm specialization in generic programming: challenges of constrained generics in C++
CFD Analysis of Axial Flow Fans with Skewed Blades
CoQoS: Coordinating QoS-aware shared resources in NoC-based SoCs