亚博买球baogaotimu:
error estimates of residual minimization using neural networks for linear pdes
亚博买球baogaoren:
professor zhongqiang zhang
亚博买球baogaoshijian:
2020nian12yue17ri 10:00—12:30
亚博买球baogaodidian:
tengxunhuiyi 846821131
报告摘要:
We propose an abstract framework for analyzing the convergence of least-squares methods based on residual minimization when feasible solutions are neural networks. With the norm relations and compactness arguments, we derive error estimates for both continuous and discrete formulations of residual minimization in strong and weak forms. The formulations cover recently developed physics-informed neural networks based on strong and variational formulations. This is a joint work with Yeonjong Shin and George Em Karniadakis at Brown University. The full text of our work can be found at
亚博买球http://arxiv.org/abs/2010.08019
baogaorenjianjie:
zhangzhongqiangjiaoshou， xianjiuzhiyuwusiteligongxueyuan（meiguo）shuxuekexuexi。2011nianshanghaidaxueshuxuexiqudejisuanshuxueboshi， shicongmahepingjiaoshou。 2014nian1yuehuodebulangdaxueyingyongshuxuexiboshixuewei，binghuodedavid gottlieb biyejiang。 2014nian7yueqirenjiaoyuwusiteligongxueyuanshuxuekexuexi。zhuyaoyanjiuxingqubaokuojiweifenfangchengshuzhijie，jisuangailvheyouhua，yijijiqixuexidejisuanlilundeng。zaigeleizhumingjisuanshuxueqikansinum, nm, sisc, jcpdengfabiaoduopianlunwen。yidiyizuozheyuprofessor george em karniadakiszhehezhunumerical methods for stochastic partial differential equations with white noise yishu。
