Machine Learning Visualization Tool for Exploring Parameterized Hydrodynamics

20 June 2024

Papers citing "Machine Learning Visualization Tool for Exploring Parameterized Hydrodynamics"

7 / 7 papers shown

Title
A Synergistic Framework Leveraging Autoencoders and Generative Adversarial Networks for the Synthesis of Computational Fluid Dynamics Results in Aerofoil Aerodynamics Tanishk Nandal Vaibhav Fulara R. Singh AI4CE 33 2 0 28 May 2023
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 541 42,591 0 03 Dec 2019
Latent-space Physics: Towards Learning the Temporal Evolution of Fluid Flow S. Wiewel M. Becher N. Thürey AI4CE 95 276 0 27 Feb 2018
Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour Priya Goyal Piotr Dollár Ross B. Girshick P. Noordhuis Lukasz Wesolowski Aapo Kyrola Andrew Tulloch Yangqing Jia Kaiming He 3DH 128 3,685 0 08 Jun 2017
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford Luke Metz Soumith Chintala GAN OOD 271 14,023 0 19 Nov 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 465 43,341 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014