Dynamical Wasserstein Barycenters for Time Series Modeling

Related tags

Deep LearningDynamicalWassBarycenters_Gaussian
Overview

Dynamical Wasserstein Barycenters for Time Series Modeling

This is the code related for the Dynamical Wasserstein Barycenter model published in Neurips 2021.

To run the code and replicate the results reported in our paper,

# usage: DynamicalWassersteinBarycenters.py dataSet dataFile debugFolder interpModel [--ParamTest PARAMTEST] [--lambda LAM] [--s S]

# Sample run on MSR data                                         
>> python DynamicalWassersteinBarycenters.py MSR_Batch ../Data/MSR_Data/subj090_1.mat ../debug/MSR/subj001_1.mat Wass 

# Sample run for parameter test
>> python DynamicalWassersteinBarycenters.py MSR_Batch ../Data/MSR_Data/subj090_1.mat ../debug/ParamTest/subj001_1.mat Wass --ParamTest 1 --lambda 100 --s 1.0

The interpMethod is either Wass` for the Wasserstein barycentric model or GMM`` for the linear interpolation model.

Simulated Data

The simulated data and experiment included in this supplement can be replicated using using the following commands.

# Generate 2 and 3 state simulated data                                         
>> python GenerateOptimizationExperimentData.py
>> python GenerateOptimizationExperimentData_3K.py

# usage: OptimizationExperiment.py FileIn Mode File
# Sample run for optimization experiment
>> python OptimizationExperiment.py ../data/SimulatedOptimizationData_2K/dim_5_5.mat/ WB ../debug/SimulatedData/dim_5_5_out.mat

The Mode is either WB for Wasserstein-Bures geometry and Euc for Euclidean geometry using Cholesky decomposition parameterization.

Requirements

_libgcc_mutex=0.1=conda_forge
_openmp_mutex=4.5=1_llvm
_pytorch_select=0.2=gpu_0
blas=2.17=openblas
ca-certificates=2020.12.5=ha878542_0
certifi=2020.12.5=py38h578d9bd_1
cffi=1.14.4=py38h261ae71_0
cudatoolkit=8.0=3
cudnn=7.1.3=cuda8.0_0
cycler=0.10.0=py_2
freetype=2.10.4=h7ca028e_0
future=0.18.2=py38h578d9bd_3
immutables=0.15=py38h497a2fe_0
intel-openmp=2020.2=254
joblib=1.0.0=pyhd8ed1ab_0
jpeg=9d=h36c2ea0_0
kiwisolver=1.3.1=py38h82cb98a_0
lcms2=2.11=hcbb858e_1
ld_impl_linux-64=2.33.1=h53a641e_7
libblas=3.8.0=17_openblas
libcblas=3.8.0=17_openblas
libedit=3.1.20191231=h14c3975_1
libffi=3.3=he6710b0_2
libgcc-ng=9.3.0=h5dbcf3e_17
libgfortran-ng=7.3.0=hdf63c60_0
libgomp=9.3.0=h5dbcf3e_17
liblapack=3.8.0=17_openblas
liblapacke=3.8.0=17_openblas
libopenblas=0.3.10=pthreads_hb3c22a3_4
libpng=1.6.37=h21135ba_2
libstdcxx-ng=9.3.0=h6de172a_18
libtiff=4.1.0=h4f3a223_6
libwebp-base=1.1.0=h36c2ea0_3
llvm-openmp=11.0.0=hfc4b9b4_1
lz4-c=1.9.2=he1b5a44_3
matplotlib-base=3.3.3=py38h5c7f4ab_0
mkl=2020.4=h726a3e6_304
mkl-service=2.3.0=py38he904b0f_0
mkl_fft=1.3.0=py38h5c078b8_1
mkl_random=1.2.0=py38hc5bc63f_1
ncurses=6.2=he6710b0_1
ninja=1.10.2=py38hff7bd54_0
numpy=1.19.5=py38h18fd61f_1
numpy-base=1.18.5=py38h2f8d375_0
olefile=0.46=pyh9f0ad1d_1
openssl=1.1.1k=h7f98852_0
pillow=8.1.0=py38h357d4e7_1
pip=20.3.3=py38h06a4308_0
pot=0.7.0=py38h950e882_0
pycparser=2.20=py_2
pyparsing=2.4.7=pyh9f0ad1d_0
python=3.8.5=h7579374_1
python-dateutil=2.8.1=py_0
python_abi=3.8=1_cp38
pytorch=1.7.1=cpu_py38h36eccb8_1
readline=8.0=h7b6447c_0
scikit-learn=0.24.1=py38h658cfdd_0
scipy=1.5.2=py38h8c5af15_0
setuptools=51.1.2=py38h06a4308_4
six=1.15.0=py38h06a4308_0
sqlite=3.33.0=h62c20be_0
threadpoolctl=2.1.0=pyh5ca1d4c_0
tk=8.6.10=hbc83047_0
tornado=6.1=py38h497a2fe_1
wheel=0.36.2=pyhd3eb1b0_0
xz=5.2.5=h7b6447c_0
zlib=1.2.11=h7b6447c_3
zstd=1.4.5=h6597ccf_2
Owner
GitHub Repository
3D ResNets for Action Recognition (CVPR 2018)

3D ResNets for Action Recognition Update (2020/4/13) We published a paper on arXiv. Hirokatsu Kataoka, Tenga Wakamiya, Kensho Hara, and Yutaka Satoh,

Kensho Hara 3.5k Jan 06, 2023
Employee-Managment - Company employee registration software in the face recognition system

Employee-Managment Company employee registration software in the face recognitio

Alireza Kiaeipour 7 Jul 10, 2022
[SIGGRAPH Asia 2021] Pose with Style: Detail-Preserving Pose-Guided Image Synthesis with Conditional StyleGAN

Pose with Style: Detail-Preserving Pose-Guided Image Synthesis with Conditional StyleGAN [Paper] [Project Website] [Output resutls] Official Pytorch i

Badour AlBahar 215 Dec 17, 2022
Meta-learning for NLP

Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks Code for training the meta-learning models and fine-tuning on downstr

IESL 43 Nov 08, 2022
Extension to fastai for volumetric medical data

FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari

Keno 26 Aug 22, 2022
🏖 Keras Implementation of Painting outside the box

Keras implementation of Image OutPainting This is an implementation of Painting Outside the Box: Image Outpainting paper from Standford University. So

Bendang 1.1k Dec 10, 2022
HNECV: Heterogeneous Network Embedding via Cloud model and Variational inference

HNECV This repository provides a reference implementation of HNECV as described in the paper: HNECV: Heterogeneous Network Embedding via Cloud model a

4 Jun 28, 2022
Leaderboard, taxonomy, and curated list of few-shot object detection papers.

Leaderboard, taxonomy, and curated list of few-shot object detection papers.

Gabriel Huang 70 Jan 07, 2023
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
Deep Latent Force Models

Deep Latent Force Models This repository contains a PyTorch implementation of the deep latent force model (DLFM), presented in the paper, Compositiona

Tom McDonald 5 Oct 26, 2022
Character-Input - Create a program that asks the user to enter their name and their age

Character-Input Create a program that asks the user to enter their name and thei

PyLaboratory 0 Feb 06, 2022
UI2I via StyleGAN2 - Unsupervised image-to-image translation method via pre-trained StyleGAN2 network

We proposed an unsupervised image-to-image translation method via pre-trained StyleGAN2 network. paper: Unsupervised Image-to-Image Translation via Pr

208 Dec 30, 2022
Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021

Spatial-Temporal Transformer for Dynamic Scene Graph Generation Pytorch Implementation of our paper Spatial-Temporal Transformer for Dynamic Scene Gra

Yuren Cong 119 Jan 01, 2023
DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.

Responsible Machine Learning With Great Power Comes Great Responsibility. Voltaire (well, maybe) How to develop machine learning models in a responsib

Model Oriented 590 Dec 26, 2022
Colab notebook and additional materials for Python-driven analysis of redlining data in Philadelphia

RedliningExploration The Google Colaboratory file contained in this repository contains work inspired by a project on educational inequality in the Ph

Benjamin Warren 1 Jan 20, 2022
Make your first PR. A beginner friendly repository made specifically for open source beginners. Add any program under any language (it can be anything from a simple program to a complex data structure algorithm). Happy coding...

Hacktober Fest 2021 Upload Different Types of Programs in any Language Use this project to make your first contribution to an open source project on G

Namish Khanna 40 Oct 11, 2022
Subgraph Based Learning of Contextual Embedding

SLiCE Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks Dataset details: We use four public benchmark da

Pacific Northwest National Laboratory 27 Dec 01, 2022
Includes PyTorch -> Keras model porting code for ConvNeXt family of models with fine-tuning and inference notebooks.

ConvNeXt-TF This repository provides TensorFlow / Keras implementations of different ConvNeXt [1] variants. It also provides the TensorFlow / Keras mo

Sayak Paul 87 Dec 06, 2022
Official Repository for Machine Learning class - Physics Without Frontiers 2021

PWF 2021 Física Sin Fronteras es un proyecto del Centro Internacional de Física Teórica (ICTP) en Trieste Italia. El ICTP es un centro dedicado a fome

36 Aug 06, 2022
A framework for the elicitation, specification, formalization and understanding of requirements.

A framework for the elicitation, specification, formalization and understanding of requirements.

NASA - Software V&V 161 Jan 03, 2023