AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...
A collaborative approach to training AI models can yield better results, but it requires finding partners with data that ...
Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, methicillin-resistant Staphylococcus aureus (MRSA) accounted for more than 100,000 global ...
A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...
Foreign exchange markets are shaped by liquidity fluctuations, which can trigger return volatility and price jumps. Identifying and predicting abnormal FX returns is critical for risk management and ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
Machine learning to identify the factors that may determine the age of onset of Huntington’s disease
A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona ...
Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility ...
An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.
Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
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