A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining th…
Genetic Programming: A Novel Computing Approach in Modeling Water Flows
A Physiological Approach to Affective Computing
Computational Emotion Model for Virtual Characters
This book constitutes the proceedings of the 21st International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2018, which took place in Thessaloniki, Greece, in April 2018, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2018.The 31 papers presented in this volume were carefully reviewed and selected from 103 submissi…
Multi-Scale Modeling and Analysis of Left Ventricular Remodeling Post Myocardial Infarction: Integration of Experimental and Computational Approaches
Discovery of Words: towards a Computational Model of Language Acquisition
Discovery of Words: towards a Computational Model of Language Acquisition
Efficient Transformation Estimation Using Lie Operators: Theory, Algorithms, and Computational Efficiencies