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Machine Learning Meets Quantum Physics

1st ed. 2020., 2020

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Learning Representations of Molecules and Materials with Atomistic Neural Networks

Machine Learning Meets Quantum Physics, p.215-230

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Solver Independent Rotating Workforce Scheduling

Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2018, Vol.10848, p.429-445

2018

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Time Table Edge Finding with Energy Variables

Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2019, Vol.11494, p.633-642

2019

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Message Passing Neural Networks

Machine Learning Meets Quantum Physics, p.199-214

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Molecular Dynamics with Neural Network Potentials

Machine Learning Meets Quantum Physics, p.233-252

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Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Machine Learning Meets Quantum Physics, p.99-127

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Accurate Molecular Dynamics Enabled by Efficient Physically Constrained Machine Learning Approaches

Machine Learning Meets Quantum Physics, p.129-154

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Machine Learning for Molecular Dynamics on Long Timescales

Machine Learning Meets Quantum Physics, p.331-372

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Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights

Machine Learning Meets Quantum Physics, p.277-307

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Introduction to Neural Networks

Machine Learning Meets Quantum Physics, p.37-62

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Efficient Synchronization of Replicated Data in Distributed Systems

Computational Science — ICCS 2003, p.274-283

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Bayesian Optimization in Materials Science

Machine Learning Meets Quantum Physics, p.413-426

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Database-Driven High-Throughput Calculations and Machine Learning Models for Materials Design

Machine Learning Meets Quantum Physics, p.377-395

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Physical Extrapolation of Quantum Observables by Generalization with Gaussian Processes

Machine Learning Meets Quantum Physics, p.171-194

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Building Nonparametric n-Body Force Fields Using Gaussian Process Regression

Machine Learning Meets Quantum Physics, p.67-98

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Polymer Genome: A Polymer Informatics Platform to Accelerate Polymer Discovery

Machine Learning Meets Quantum Physics, p.397-412

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High-Dimensional Neural Network Potentials for Atomistic Simulations

Machine Learning Meets Quantum Physics, p.253-275

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Quantum Machine Learning with Response Operators in Chemical Compound Space

Machine Learning Meets Quantum Physics, p.155-169

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Introduction to Material Modeling

Machine Learning Meets Quantum Physics, p.7-24

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Kernel Methods for Quantum Chemistry

Machine Learning Meets Quantum Physics, p.25-36

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Active Learning and Uncertainty Estimation

Machine Learning Meets Quantum Physics, p.309-329

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Recommender Systems for Materials Discovery

Machine Learning Meets Quantum Physics, p.427-443

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A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects

Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2021, Vol.12735, p.26-44

2021

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Learning Value Heuristics for Constraint Programming

Integration of AI and OR Techniques in Constraint Programming, 2015, Vol.9075, p.108-123

2015

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Machine Learning Meets Quantum Physics

Learning Representations of Molecules and Materials with Atomistic Neural Networks

Solver Independent Rotating Workforce Scheduling

Time Table Edge Finding with Energy Variables

Message Passing Neural Networks

Molecular Dynamics with Neural Network Potentials

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Accurate Molecular Dynamics Enabled by Efficient Physically Constrained Machine Learning Approaches

Machine Learning for Molecular Dynamics on Long Timescales

Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights

Introduction to Neural Networks

Efficient Synchronization of Replicated Data in Distributed Systems

Bayesian Optimization in Materials Science

Database-Driven High-Throughput Calculations and Machine Learning Models for Materials Design

Physical Extrapolation of Quantum Observables by Generalization with Gaussian Processes

Building Nonparametric n-Body Force Fields Using Gaussian Process Regression

Polymer Genome: A Polymer Informatics Platform to Accelerate Polymer Discovery

High-Dimensional Neural Network Potentials for Atomistic Simulations

Quantum Machine Learning with Response Operators in Chemical Compound Space

Introduction to Material Modeling

Kernel Methods for Quantum Chemistry

Active Learning and Uncertainty Estimation

Recommender Systems for Materials Discovery

A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects

Learning Value Heuristics for Constraint Programming

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