Predicting Porosity, Permeability, and Tortuosity of Porous Media from Images by Deep Learning

6 July 2020

Papers citing "Predicting Porosity, Permeability, and Tortuosity of Porous Media from Images by Deep Learning"

5 / 5 papers shown

Title
PDE-NetGen 1.0: from symbolic PDE representations of physical processes to trainable neural network representations O. Pannekoucke Ronan Fablet AI4CE PINN DiffM 26 8 0 03 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 287 42,038 0 03 Dec 2019
A high-bias, low-variance introduction to Machine Learning for physicists Pankaj Mehta Marin Bukov Ching-Hao Wang A. G. Day C. Richardson Charles K. Fisher D. Schwab AI4CE 72 870 0 23 Mar 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 369 2,922 0 15 Sep 2016
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 356 43,154 0 11 Feb 2015