2UrbanGirls on MSNOpinion
Neel Somani on formal methods and the future of machine learning safety
Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...
Morning Overview on MSN
Machine learning is turbocharging cheap lithium-ion battery design
Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...
Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...
The question of whether prehospital emergency anaesthesia and intubation improves survival in patients with major trauma has ...
High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...
RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.
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