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amcparser

Parse and visualize asf/amc files from CMU MoCap dataset.

bds-articles

Article code from Better Data Science and Medium

brits

Code of NIPS18 Paper: BRITS: Bidirectional Recurrent Imputation for Time Series

bvh-toolbox

Scripts for manipulating and converting BVH files.

cpsc330

CPSC 330: Applied Machine Learning

data-science-from-scratch

code for Data Science From Scratch book

generative_adversarial_imputation_networks

Codebase for Generative Adversarial Imputation Networks (GAIN) - ICML 2018

interview_python

关于Python的面试题

latent_ode

Code for "Latent ODEs for Irregularly-Sampled Time Series" paper

mdcrqa

This repository contains R and Matlab functions for the computation of Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) from the paper "Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) – a method for quantifying correlation between multivariate time-series."

mocap-refinement

This repository includes implementation codes or links to the authors’ original codes of filtering methods for denoising and completing data generated by software platforms for human motion analysis, allowing readers to easily reproduce all the algorithms in different experimental settings.

mocap-solver

mtsit

Codes for: "Multivariate Time Series Imputation with Transformers"

mvts_transformer

Multivariate Time Series Transformer, public version

nn-for-missing-marker-reconstruction

This is the official implementation of the paper "A Neural Network Approach to Missing Marker Reconstruction in Human Motion Capture"

smplify-x

Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

soma

Solving Optical MoCap Automatically

spektral

Graph Neural Networks with Keras and Tensorflow 2.

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

time_series_gan

Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019

uc_berkeley_ai_projects_1

wgan_financial_timeseries

Thesis project done on Generation Financial Time-Series with GANs. The project was a collaboration between Wholesale Banking Advanced Analytics team with ING and University Maastricht.