Data-driven approaches for predicting spread of infectious diseases through DINNs: Disease Informed Neural Networks

11 October 2021

Papers citing "Data-driven approaches for predicting spread of infectious diseases through DINNs: Disease Informed Neural Networks"

7 / 7 papers shown

Title
X-IL: Exploring the Design Space of Imitation Learning Policies Xiaogang Jia Atalay Donat Xi Huang Xuan Zhao Denis Blessing ... Han A. Wang Hanyi Zhang Qian Wang Rudolf Lioutikov Gerhard Neumann 91 1 0 20 Feb 2025
MP-PINN: A Multi-Phase Physics-Informed Neural Network for Epidemic Forecasting T. Nguyen D. Nguyen K. Pham T. Tran 39 0 0 11 Nov 2024
A model learning framework for inferring the dynamics of transmission rate depending on exogenous variables for epidemic forecasts Giovanni Ziarelli S. Pagani N. Parolini Francesco Regazzoni M. Verani 26 0 0 15 Oct 2024
PINN Training using Biobjective Optimization: The Trade-off between Data Loss and Residual Loss Fabian Heldmann Sarah Treibert Matthias Ehrhardt K. Klamroth 38 20 0 03 Feb 2023
Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries Pengfei Wen Z. Ye Yong Li Shaowei Chen Pu Xie Shuai Zhao 30 35 0 02 Jan 2023
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
Generalizing to New Physical Systems via Context-Informed Dynamics Model Matthieu Kirchmeyer Yuan Yin Jérémie Donà Nicolas Baskiotis A. Rakotomamonjy Patrick Gallinari OOD AI4CE 24 32 0 01 Feb 2022