A deep learning approach to optimize remaining useful life prediction for Li-ion batteries
This section presents the details of the proposed predictive model, AccuCell Prodigy. The AccuCell Prodigy model includes auto-encoders and LSTM...
Learning
Google AI Introduces Iterative BC-Max: A New Machine Learning Technique that Reduces the Size of Compiled Binary Files by Optimizing Inlining Decisions
When applying Reinforcement Learning (RL) to real-world applications, two key challenges are often faced during this process. Firstly, the constant...
Estimation of hydrogen solubility in aqueous solutions using machine learning techniques for hydrogen storage in deep saline aquifers
Qureshi, R. A. et al. Facile eggplant assisted mixed metal oxide nanostructures: a promising electrocatalyst for water oxidation in alkaline...
Promises and challenges of generative artificial intelligence for human learning
Gašević, D., Siemens, G. & Sadiq, S. Empowering learners for the age of artificial intelligence. Comput. Educ. Artif. Intell. 4,...
Predictive ability of hypotension prediction index and machine learning methods in intraoperative hypotension: a systematic review and meta-analysis | Journal of Translational Medicine
Weiser TG, Haynes AB, Molina G, Lipsitz SR, Esquivel MM, Uribe-Leitz T, et al. Estimate of the global volume of...
Reinforcement learning pentesting agent training in realistic network environments
Overview of the PenGym framework architecture. Credit: Razvan Beuran from JAIST. Ensuring the security of network systems and infrastructure is...
