Have you ever witnessed an equity index trade in a peaceful, tight consolidation range for hours, only to violently accelerate into a chaotic, high-velocity sell-off the exact moment a specific, ...

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

Precision has long been the central bottleneck of analogue computing. Bit-slicing or analogue compensation can be used to perform matrix–vector multiplication with precision, but solving matrix ...

1 Tianjin Engineering Research Center of Civil Aviation Energy Environment and Green Development, Civil Aviation University of China, Tianjin, China. 2 Groupe d’Acoustigue de l’ Université de ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Abstract: This letter propose a quasi-Newton based weighted minimum mean square error (WMMSE) algorithm without matrix inverse to solve the weighted sum rate (WSR ...

Implements selected inverse reinforcement learning (IRL) algorithms as part of COMP3710, supervised by Dr Mayank Daswani and Dr Marcus Hutter. My final report is available here and describes the ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...

Introduction: Triply periodic minimal surface (TPMS) is widely used in the design of bone scaffolds due to its structural advantages. However, the current approach to designing bone scaffolds using ...

Geophysical inverse problems face a lot of issues to be solved, e.g., data noise problems: the general data records contain a lot of noise due to various factors in the excitation, propagation and ...

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