Seq2seq Time-Feature Analysis using an Encoder-Decoder to project into latent space and a Forward Network to predict the next sequence, based on Tensorflow.
segen is a model for sequence generalization using the “network” of similarities among sequences for the extrapolation
Naive is a model to extract the common patterns from sequences and extrapolate time features
dymo proposes an implementation of Dynamic Mode Decomposition (SVD-approach) to predict multiple time features
Dynamic regression for time series using Extreme Gradient Boosting with hyper-parameter tuning via Bayesian Optimization or Random Search.
Automatic fast extrapolation of time features using kNN.
Time features extrapolation through spectral analysis and jack-knife resampling.
Model for sequence forecasting based on expansion of distance matrix.
SNAP is a tool to design deep neural network with a single line of code.
Proteus is a Sequence-to-Sequence Variational Model for time-feature analysis based on a wide range of different distributions.