Artificial Intelligence for Science
Computational Approaches to Scientific Discovery
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Beschreibung
AI systems will support scientists by expanding the scope of inquiry, accelerating the generation and testing of hypotheses, and making possible forms of experimentation and analysis that would otherwise be impractical.
By presenting complementary perspectives on automated discovery, equation discovery, and modelling dynamical systems, this volume offers both an account of current progress and a foundation for further research into how intelligent systems can contribute responsibly and creatively to science.
AI systems will support scientists by expanding the scope of inquiry, accelerating the generation and testing of hypotheses, and making possible forms of experimentation and analysis that would otherwise be impractical.
By presenting complementary perspectives on automated discovery, equation discovery, and modelling dynamical systems, this volume offers both an account of current progress and a foundation for further research into how intelligent systems can contribute responsibly and creatively to science.
Valuable for all researchers engaged with how AI tools can accelerate scientific discovery and technical developments Timely contributions explain the context and the full set of established and new Machine Learning approaches Advances in AI, machine learning, robotics, data science, and knowledge engineering are reshaping scientific discovery
Autor*in
Saso Dzeroski
Themen in »Artificial Intelligence for Science«
Machine Learning (ML) Scientific Discovery Knowledge Disovery Data science Data-driven scientific discovery Knowlege-driven scientific discovery Artificial Intelligence (AI)