Machine Learning on Sequential Data Using a Recurrent Weighted Average

pathpy is an OpenSource python package for the modeling and analysis of pathways and temporal networks using higher-order and multi-order graphical models

Real-time Recognition of german sign language (DGS) with MediaPipe

Peax is a tool for interactive visual pattern search and exploration in epigenomic data based on unsupervised representation learning with autoencoders

Tensorflow Implementation of GAN modeling for sequential data

A fast, scalable and light-weight C++ Fréchet and DTW distance library, exposed to python and focused on clustering of polygonal curves.

Sequential sets to sequential sets learning

Simplified Python implementation of the Density Line Chart by Moritz & Fisher.

PyTorch re-implementation of [Structured Inference Networks for Nonlinear State Space Models, AAAI 17]

Performed various Deep Learning techniques to detect Human Activity using Sequential Data detect human activities generated by sensor-based wearable devices

Benchmarking synthetic data generators for sequential data in terms of accuracy and privacy.

This repository contains PyTorch implementations of Neural Process, Attentive Neural Process, and Recurrent Attentive Neural Process.

Code for Probabilistic Sequential Matrix Factorization

Generic Motoko library for sequential data

Incremental Label Propagation (ILP) - Incremental Semi-Supervised Learning from Streams for Object Classification

Data loader and model for variable length data in PyTorch

Feature extraction from sequential data

Lexis: An Optimization Framework for Discovering the Hierarchical Structure of Sequential Data

Warped K-Means

Exact HMM inference in C++20. Baum-Welch EM, Viterbi, posterior decoding, 15 emission distributions, SIMD-accelerated. Zero external dependencies.