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.

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...

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 ...

Swarm Network has announced the closing of a $13 million funding round that will expedite the development of its decentralized AI verification protocol. Part of the round was collected via a $10 ...

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 ...

Researchers from China’s Shenyang Agricultural University have developed a novel maximum power point tracking (MPPT) technique for PV systems operating under partial shading. Their new method is an ...

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 ...