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New AI systems are teaching machines to verifiably function safely
From industrial robots to self-driving cars, engineers face a common problem: keeping machines steady and predictable. When ...
Some questions in the exam will require you to recall and apply equations you have learned in class. Other questions will ask you to use the ‘Physics Equation Sheet’. This is a set list of equations ...
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AI techniques excel at solving complex equations in physics, especially inverse problems
Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...
Quantum entanglement is one seriously long-distance relationship. Quantum entanglement occurs when two subatomic particles become linked in such a way that their properties remain connected, no matter ...
Multi-Scale Feature Fusion Based on Piecewise Polynomial Activation Function for Image-Text matching
Abstract: Image-text matching remains challenging in big data processing. Matching accuracy is influenced by various factors, including the correlation between images and texts, feature extraction and ...
Abstract: The technique of solving differential equations using Physics-Informed Neural Networks (PINNs) has received extensive attention and application. However, employing neural networks with ...
Superposition and Entanglement. Alright, let’s talk about what makes quantum computing so different from the computers we use ...
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