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pro vyhledávání: '"Low, Jonathan Sze Choong"'
The modeling of dynamical systems is a pervasive concern for not only describing but also predicting and controlling natural phenomena and engineered systems. Current data-driven approaches often assume prior knowledge of the relevant state variables
Externí odkaz:
http://arxiv.org/abs/2408.11691
Interleaved practice enhances the memory and problem-solving ability of students in undergraduate courses. We introduce a personalized learning tool built on a Large Language Model (LLM) that can provide immediate and personalized attention to studen
Externí odkaz:
http://arxiv.org/abs/2407.00065
Can a machine or algorithm discover or learn the elliptical orbit of Mars from astronomical sightings alone? Johannes Kepler required two paradigm shifts to discover his First Law regarding the elliptical orbit of Mars. Firstly, a shift from the geoc
Externí odkaz:
http://arxiv.org/abs/2312.12315
Many functions characterising physical systems are additively separable. This is the case, for instance, of mechanical Hamiltonian functions in physics, population growth equations in biology, and consumer preference and utility functions in economic
Externí odkaz:
http://arxiv.org/abs/2312.09775
Can a machine or algorithm discover or learn Kepler's first law from astronomical sightings alone? We emulate Johannes Kepler's discovery of the equation of the orbit of Mars with the Rudolphine tables using AI Feynman, a physics-inspired tool for sy
Externí odkaz:
http://arxiv.org/abs/2312.09766
Hamiltonian neural networks (HNNs) are state-of-the-art models that regress the vector field of a dynamical system under the learning bias of Hamilton's equations. A recent observation is that embedding a bias regarding the additive separability of t
Externí odkaz:
http://arxiv.org/abs/2309.01069
Publikováno v:
In Procedia CIRP 2024 122:115-120
Publikováno v:
In Resources, Conservation & Recycling September 2023 196
Publikováno v:
In Resources, Conservation & Recycling January 2023 188
Autor:
Lee, Yinjin, Goh, Soo Lin, Hsien, Cadence, Choy, Sing Ying, Tay, Terence Wei Rong, Cardelle, Marianela, Chan, Chris, Yeo, Zhiquan, Hauser, Andreas, Low, Jonathan Sze Choong
Publikováno v:
In Procedia CIRP 2023 116:342-347