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 ...
At Pittcon 2026 in San Antonio, Texas, USA, LCGC International spoke with 2026 LCGC International Emerging Leader Award ...
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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 ...
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 ...
Methane is one of the most powerful greenhouse gases, yet quantifying its emissions remains difficult at large scales. A new framework, CH4Vision, addresses this problem by estimating methane flux ...
HIV-1 envelope glycoprotein (Env), a gp120–gp41 trimer, undergoes coordinated conformational changes that drive membrane fusion and allow immune evasion by transiently concealing ...
RT-MALS can provide instantaneous measurements of adenovirus particle size and titer during downstream and fill–finish ...
Visualization, Dimensionality Reduction, Reproducibility, Stability, Multivariate Quantum Data, Information Retrieval ...
New to gravel racing? Here are the key differences between the same bike set up for a rider’s first gravel race versus their 50th.
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