A collaborative approach to training AI models can yield better results, but it requires finding partners with data that ...
Research reveals that knowledge distillation significantly compensates for sensor drift in electronic noses, improving ...
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.
AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...
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 ...
ctDNA versus 18F-FDG PET-CT in predicting long-term disease control in patients with advanced melanoma undergoing immune checkpoint blockade therapy. Delineating the role of the microbiome and tumor ...
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 ...
Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...
Estimating the location of contact is a primary function of artificial tactile sensing apparatuses that perceive the environment through touch. Existing contact localization methods use flat geometry ...
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