Abstract: In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing. The success of ...
TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.
Abstract: The reversible residual neural network (RRNN) model is a bidirectional neural network model, which has recently gained attention in the design of various control methods in turntable servo ...
where the output is not from a fixed vocabulary, but a sequence of pointers to elements from the input. Main idea: Instead of producing an output token from a fixed-size vocabulary, the model points ...
Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations — it’s a triumph of your associative memory, in which one piece of information (the first few ...
Researchers at Ben-Gurion University of the Negev have developed a machine-learning algorithm that could enhance our understanding of human biology and disease. The new method, Weighted Graph ...
1 Energy, Materials and Methods Research Laboratory, National High Polytechnic School of Douala, Douala, Cameroon. 2 National Advanced School of Engineering, University of Yaounde I, Yaounde, Cameroon ...
In recent years, due to rapid fossil fuel depletion (Peng et al., 2020), booming global energy demand (Shangguan et al., 2020a), and a series of severe eco-environmental problems (Yang et al., 2015), ...
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