EPFL researchers have developed a groundbreaking algorithm that efficiently trains analog neural networks, offering an energy-efficient alternative to traditional digital networks. This method, which aligns more closely with human learning, has shown promising results in wave-based physical systems and ...
A comprehensive introduction to the fundamentals of machine learning is also provided, including open-source databases, feature engineering, machine learning algorithms, and analysis of machine learning model. Afterwards, the latest progress in data-driven materials science and engineering, including ...
Advanced Intelligent Systems Advanced Intelligent Systems (AISY)旨在提供一个新的高质量开放获取知识的平台,发表经同行评议的高质量高影响力研究论文,内容涵盖Artificial Intelligence, Machine Learning,Robotics,Control Systems, Automation,Smart Sensing Systems,Directed Self-Assembly,Neuromorphic Engineering,Quantum Compu...
Advanced Intelligent Systems (AISY)旨在提供一个新的高质量开放获取知识的平台,发表经同行评议的高质量高影响力研究论文,内容涵盖Artificial Intelligence,Machine Learning,Robotics,Control Systems,Automation,Smart Sensing Systems,Directed Self-Assembly,...
In CORTEX, it was demonstrated that, for large PWRs, machine learning-based unfolding of the measured neutron noise could correctly identify different types of perturbations and, when relevant, successfully localize such fluctuations. In terms of localization of the noise source, the method can predic...
These artificial intelligence methods include mathematical modeling, chemometrics, machine learning, deep learning, and artificial neural networks. In general, advanced detection techniques incorporating artificial intelligence have not yet penetrated into all aspects of commercial berry processing, which include...
Jean-Philippe Thiran, EPFL, Lausanne, Switzerland. Nadège Thirion-Moreau, SeaTech - Université de Toulon, Toulon, France. Sylvie Treuillet, Université d'Orléans, Orléans, France. Luisa Verdoliva, Universita Degli Studi di Napoli, Napoli, Italy. ...
2024 SBIR/STTR AGENCY PARTNERS
- Marcel Salathé (EPFL) * 7 Tutorials: - Project Management for Data Science - Deep Learning for Computer Vision: A practitioner’s viewpoint - Data Science Workflows Using R and Spark - Kernel Methods for Machine Learning and Data Science ...
最新的生物学发现表明,静止的“锁和钥匙”理论并不普遍适用,原子位点和结合姿势的变化可以为理解药物结合提供重要信息。然而,计算开销限制了蛋白质轨迹相关研究的发展,从而阻碍了监督学习的可能性。本文提出了一种基于改进的等变图匹配网络的时空预训练模型,称为 ProtMD,它包含两个自监督学习任务:原子级基于提示的去噪...