Forecasting Hamiltonian dynamics without canonical coordinates
Sign Up to like & getrecommendations! Published in 2020 at "Nonlinear Dynamics"
DOI: 10.1007/s11071-020-06185-2
Abstract: Conventional neural networks are universal function approximators, but they may need impractically many training data to approximate nonlinear dynamics. Recently introduced Hamiltonian neural networks can efficiently learn and forecast dynamical systems that conserve energy, but… read more here.
Keywords: hamiltonian dynamics; without canonical; dynamics without; pendulum ... See more keywords
Abstract 2055: Prevalent focal amplification of oncogene in lung adenocarcinomas without canonical driver alterations
Sign Up to like & getrecommendations! Published in 2023 at "Cancer Research"
DOI: 10.1158/1538-7445.am2023-2055
Abstract: Lung adenocarcinoma (LADC) is the most common type of lung cancer and a leading cause of death worldwide. Typical oncogenes that drive LADCs when mutated (referred to as canonical drivers) include EGFR (30-60%), KRAS (10-30%),… read more here.
Keywords: lung adenocarcinomas; prevalent focal; lung; canonical drivers ... See more keywords