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Andrew Yan-Tak Ng (Chinese: 吳恩達; born April 18, 1976 [2]) is a British-American computer scientist and technology entrepreneur focusing on machine learning and artificial intelligence (AI). [3] Ng was a cofounder and head of Google Brain and was the former Chief Scientist at Baidu , building the company's Artificial Intelligence Group ...
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).
Coursera Inc. (/ k ər ˈ s ɛ r ə /) is an American global massive open online course provider. It was founded in 2012 [2] [3] by Stanford University computer science professors Andrew Ng and Daphne Koller. [4] Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects.
Daphne Koller (Hebrew: דפנה קולר; born August 27, 1968) is an Israeli-American computer scientist. She was a professor in the department of computer science at Stanford University [4] and a MacArthur Foundation fellowship recipient. [1]
Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research.A basic example of this is quantum state tomography, where a quantum state is learned from measurement. [1]
An energy-based model (EBM) (also called Canonical Ensemble Learning or Learning via Canonical Ensemble – CEL and LCE, respectively) is an application of canonical ensemble formulation from statistical physics for learning from data. The approach prominently appears in generative artificial intelligence.
The material point method (MPM) is a numerical technique used to simulate the behavior of solids, liquids, gases, and any other continuum material. Especially, it is a robust spatial discretization method for simulating multi-phase (solid-fluid-gas) interactions.
The book outlines five approaches of machine learning: inductive reasoning, connectionism, evolutionary computation, Bayes' theorem and analogical modelling.The author explains these tribes to the reader by referring to more understandable processes of logic, connections made in the brain, natural selection, probability and similarity judgments.
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