Tensor network methods provide a structured approach to representing and manipulating high-dimensional data by decomposing global information into interconnected low-rank tensors. Originating in the ...

LLM quantization without calibration data: DualQuant from AI inference startup d-Matrix eliminates the dataset requirement ...

New computational techniques, 'HighLight' and 'Tailors and Swiftiles,' could dramatically boost the speed and performance of high-performance computing applications like graph analytics or generative ...

An extension of tensor networks—mathematical tools that simplify the study of complex quantum systems—could allow their application to a broad range of quantum field theory problems. Figure 1: Tilloy ...

Using a conventional computer and cutting-edge mathematical tools and code, physicists at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation's Flatiron Institute and ...