Machine learning for metal additive manufacturing: Predicting
temperature and melt pool fluid dynamics using physics-informed neural
networks

Machine learning for metal additive manufacturing: Predicting temperature and melt pool fluid dynamics using physics-informed neural networks

28 July 2020

Papers citing "Machine learning for metal additive manufacturing: Predicting temperature and melt pool fluid dynamics using physics-informed neural networks"

17 / 17 papers shown

Title
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 277 42,038 0 03 Dec 2019
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks Georgios Kissas Yibo Yang E. Hwuang W. Witschey John A. Detre P. Perdikaris AI4CE 101 368 0 13 May 2019
Is it Time to Swish? Comparing Deep Learning Activation Functions Across NLP tasks Steffen Eger Paul Youssef Iryna Gurevych LLMSV 44 76 0 09 Jan 2019
Exploring the 3D architectures of deep material network in data-driven multiscale mechanics Zeliang Liu C. T. Wu 3DV AI4CE 18 145 0 02 Jan 2019
Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence Xiu Yang D. Barajas-Solano G. Tartakovsky A. Tartakovsky 46 77 0 24 Nov 2018
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 54 611 0 28 Nov 2017
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 68 912 0 28 Nov 2017
Machine Learning of Linear Differential Equations using Gaussian Processes M. Raissi George Karniadakis 54 544 0 10 Jan 2017
Why Deep Neural Networks for Function Approximation? Shiyu Liang R. Srikant 73 383 0 13 Oct 2016
An overview of gradient descent optimization algorithms Sebastian Ruder ODL 177 6,170 0 15 Sep 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 338 18,300 0 27 May 2016
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction Chris Choy Danfei Xu JunYoung Gwak Kevin Chen Silvio Savarese 3DV 74 1,710 0 02 Apr 2016
Fully Connected Deep Structured Networks Alex Schwing R. Urtasun SSeg 112 308 0 09 Mar 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 132 2,775 0 20 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 854 149,474 0 22 Dec 2014
Caffe: Convolutional Architecture for Fast Feature Embedding Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross B. Girshick S. Guadarrama Trevor Darrell VLM BDL 3DV 195 14,703 0 20 Jun 2014
Theano: new features and speed improvements Frédéric Bastien Pascal Lamblin Razvan Pascanu James Bergstra Ian Goodfellow Arnaud Bergeron Nicolas Bouchard David Warde-Farley Yoshua Bengio 75 1,420 0 23 Nov 2012