Search records | 東京工業大学附属図書館蔵書検索

目次情報: 続きを見る

Preface

Intelligence Reimagined / Part I：

The Rise of Machine Learning / 1：

The Rebirth of Artificial Intelligence / 2：

The Dawn of Neural Networks / 3：

Brain-style Computing / 4：

Insights from the Visual System / 5：

Many Ways to Learn / Part II：

The Cocktail Party Problem / 6：

The Hopfield Net and Boltzmann Machine / 7：

Backpropagating Errors / 8：

Convolutional Learning / 9：

Reward Learning / 10：

Neural Information Processing Systems / 11：

Technological and Scientific Impact / Part III：

The Future of Machine Learning / 12：

The Age of Algorithms / 13：

Hello, Mr. Chips / 14：

Inside Information / 15：

Consciousness / 16：

Nature Is Cleverer Than We Are / 17：

Deep Intelligence / 18：

Acknowledgments

Recommended Reading

Glossary

Notes

Index

Preface

Intelligence Reimagined / Part I：

The Rise of Machine Learning / 1：

目次情報: 続きを見る

Preface

Atomic-Scale Representation and Statistical Learning of Tensorial Properties / Andrea Grisafi and David M. Wilkins and Michael J. Willatt and Michele Ceriotti1：

Prediction of Mohs Hardness with Machine Learning Methods Using Compositional Features / Joy C. Garnett2：

High-Dimensional Neural Network Potentials for Atomistic Simulations / Matti Hellström and Jörg Behler3：

Data-Driven Learning Systems for Chemical Reaction Prediction: An Analysis of Recent Approaches / Philippe Schwaller and Teodoro Laino4：

Using Machine Learning To Inform Decisions in Drug Discovery: An Industry Perspective / Darren V. S. Green5：

Cognitive Materials Discovery and Onset of the 5th Discovery Paradigm / Dmitry Y. Zubarev and Jed W. Pitera6：

Editors' Biographies

Indexes

Author Index

Subject Index

Preface

Atomic-Scale Representation and Statistical Learning of Tensorial Properties / Andrea Grisafi and David M. Wilkins and Michael J. Willatt and Michele Ceriotti1：

Prediction of Mohs Hardness with Machine Learning Methods Using Compositional Features / Joy C. Garnett2：

絞り込み条件: