Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers

DreamSoul

Last update: Sep 12, 2022

Related tags

Deep Learning Dimension-Reduced-Turbulent-Flow-Data-From-Deep-Vector-Quantizers

Overview

Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers

This is an implementation of A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow
This is an implementation of Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers

Requirements

see requirements.txt

Instruction

Global hyperparameters are configured in config.yml
Hyperparameters can be found at process_control() in utils.py

Examples

Train vqvae, compression scale 1, regularization parameter $\alpha=0.1,\gamma=0$

python train_vqvae.py --data_name Turb --model_name vqvae --control_name 1_exact-physcis_0.1-0

Test vqvae, compression scale 3, regularization parameter $\alpha=0.1,\gamma=0.0001$

python test_vqvae.py --data_name Turb --model_name vqvae --control_name 3_exact-physcis_0.1-0.0001

Results

Schematic of the VQ-AE architecture.

Comparing original and reconstructed 3D (a) stationary isotropic, (b) decaying isotropic, and (c) Taylor-Green vortex turbulence compressed by VQ-AE.

(a) with and (b) without regularizations for PDFs of normalized longitudinal (left), transverse (middle) components of velocity gradient tensor, and Turbulence Kinetic Energy spectra (right) of stationary isotropic turbulence flow.

Acknowledgement

Mohammadreza Momenifar
Enmao Diao
Vahid Tarokh
Andrew D. Bragg

You might also like...

Flow is a computational framework for deep RL and control experiments for traffic microsimulation.

Flow Flow is a computational framework for deep RL and control experiments for traffic microsimulation. See our website for more information on the ap

867 Jan 2, 2023

[CVPR 2022] Deep Equilibrium Optical Flow Estimation

Deep Equilibrium Optical Flow Estimation This is the official repo for the paper Deep Equilibrium Optical Flow Estimation (CVPR 2022), by Shaojie Bai*

136 Dec 18, 2022

Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021

Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom

59 Nov 24, 2022

Vector Neurons: A General Framework for SO(3)-Equivariant Networks

Vector Neurons: A General Framework for SO(3)-Equivariant Networks Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacc

332 Dec 29, 2022

General Virtual Sketching Framework for Vector Line Art (SIGGRAPH 2021)

General Virtual Sketching Framework for Vector Line Art - SIGGRAPH 2021 Paper | Project Page Outline Dependencies Testing with Trained Weights Trainin

118 Dec 27, 2022

Neural implicit reconstruction experiments for the Vector Neuron paper

Neural Implicit Reconstruction with Vector Neurons This repository contains code for the neural implicit reconstruction experiments in the paper Vecto

35 Jan 2, 2023

Geometric Vector Perceptron --- a rotation-equivariant GNN for learning from biomolecular structure

Geometric Vector Perceptron Code to accompany Learning from Protein Structure with Geometric Vector Perceptrons by B Jing, S Eismann, P Suriana, RJL T

85 Dec 29, 2022

This repository contains a set of codes to run (i.e., train, perform inference with, evaluate) a diarization method called EEND-vector-clustering.

EEND-vector clustering The EEND-vector clustering (End-to-End-Neural-Diarization-vector clustering) is a speaker diarization framework that integrates

45 Dec 26, 2022

The all new way to turn your boring vector meshes into the new fad in town; Voxels!

Voxelator The all new way to turn your boring vector meshes into the new fad in town; Voxels! Notes: I have not tested this on a rotated mesh. With fu

6 Feb 3, 2022

Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers

Related tags

Overview

Dimension Reduced Turbulent Flow Data From Deep Vector Quantizers

Requirements

Instruction

Examples

Results

Acknowledgement

You might also like...

Flow is a computational framework for deep RL and control experiments for traffic microsimulation.

[CVPR 2022] Deep Equilibrium Optical Flow Estimation

Implementation of Geometric Vector Perceptron, a simple circuit for 3d rotation equivariance for learning over large biomolecules, in Pytorch. Idea proposed and accepted at ICLR 2021

Vector Neurons: A General Framework for SO(3)-Equivariant Networks

General Virtual Sketching Framework for Vector Line Art (SIGGRAPH 2021)

Neural implicit reconstruction experiments for the Vector Neuron paper

Geometric Vector Perceptron --- a rotation-equivariant GNN for learning from biomolecular structure

This repository contains a set of codes to run (i.e., train, perform inference with, evaluate) a diarization method called EEND-vector-clustering.

The all new way to turn your boring vector meshes into the new fad in town; Voxels!

Owner

DreamSoul

Interpolation-based reduced-order models

Implementation of "Bidirectional Projection Network for Cross Dimension Scene Understanding" CVPR 2021 (Oral)

Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight

In this repo we reproduce and extend results of Learning in High Dimension Always Amounts to Extrapolation by Balestriero et al. 2021

Just Go with the Flow: Self-Supervised Scene Flow Estimation

Deep Learning Datasets Maker is a QGIS plugin to make datasets creation easier for raster and vector data.

A lightweight deep network for fast and accurate optical flow estimation.

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

Here I will explain the flow to deploy your custom deep learning models on Ultra96V2.