被ICASSP 2026接收的PINN训练新方法，提出无模块化冲突避免策略，提升泛化能力。
arXiv:2606.20156v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have become a powerful framework for solving PDEs by embeddin…
让Claude Code的旋转展示为你赚钱，轻松赚取额外收入
Article URL: https://kickbacks.ai Comments URL: https://news.ycombinator.com/item?id=48500004 Points: 2 # Comments: 0
引入损失条件机制优化PINNs训练，高效求解参数化偏微分方程族
arXiv:2606.04420v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) approximate solutions of ODEs and PDEs by minimising a weight…
揭示物理信息神经网络（PINNs）失败的根本原因——过拟合，为改进PINN训练提供新视角
arXiv:2605.30910v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) are a common class of machine learning-based partial differen…
OpenAI首次深度强化学习教育工作坊回顾，亮点在于Spinning Up项目的实践教学与社区反响。
On February 2, we held our first Spinning Up Workshop as part of our new education initiative at OpenAI.