The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my advisers, Cyrus Shahabi, had worked for many years on the problem of traffic ...

The findings are published in the Journal of Computational Physics ... deep learning on GPUs, we have reduced computation time by a factor of 1,000 compared to traditional CPU-based codes ...

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2025.240189, discusses enhanced photoacoustic microscopy ...

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2025.240189 , discusses enhanced photoacoustic microscopy with physics-embedded ...

FEM combines free-energy minimization from statistical physics with gradient-based optimization techniques in machine learning and utilizes parallel computation, outperforming state-of-the-art ...

This machine uses statistical physics principles to classify images and generate new examples based on learnt patterns. Hinton's techniques have been instrumental in advancing deep learning ...

Their study, "Deep Learning and Methods Based on Large Language Models Applied to Stellar Light Curve Classification," was published Feb. 26 in Intelligent Computing. The team introduced the ...