In this course, you’ll learn theoretical foundations of optimization methods used for training deep machine learning models. Why does gradient descent work? Specifically, what can we guarantee about ...
The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...
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How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?
Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
Researchers have developed a hybrid surrogate model for iso-octanol oxidation to iso-octanal that integrates data-driven approaches with chemical equations grounded in mass transfer, heat transfer, ...
In recent years, artificial intelligence has become more accessible than ever before. Powerful libraries, automated platforms ...
Researchers have proposed a personalized longitudinal motion planning policy for intelligent vehicles that combines reinforcement learning with imitation learning. The approach is designed to reduce ...
A platform approach to gene editing brings together design, manufacturing, validation, analytics, and regulatory considerations right from the start.
RT-MALS can provide instantaneous measurements of adenovirus particle size and titer during downstream and fill–finish ...
Automation, AI, and human organoids enable researchers to move away from outdated 2D cell cultures and animal models, ...
The dorsal S-duct inlet of a HALE blended wing body UAV faces complex unsteady disturbances during operation. This study ...
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