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giancarlo_vercellino

Giancarlo Vercellino

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Introduction to codez
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.
Introduction to segen
segen is a model for sequence generalization using the “network” of similarities among sequences for the extrapolation
Intro to naive
Naive is a model to extract the common patterns from sequences and extrapolate time features
Introduction to dymo
dymo proposes an implementation of Dynamic Mode Decomposition (SVD-approach) to predict multiple time features
Introduction to AUDREX
Dynamic regression for time series using Extreme Gradient Boosting with hyper-parameter tuning via Bayesian Optimization or Random Search.
Introduction to Jenga
Automatic fast extrapolation of time features using kNN.
Introduction to spooky
Time features extrapolation through spectral analysis and jack-knife resampling.
Tetragon: a brief introduction
Model for sequence forecasting based on expansion of distance matrix.
Introduction to SNAP
SNAP is a tool to design deep neural network with a single line of code.
Proteus: a brief introduction
Proteus is a Sequence-to-Sequence Variational Model for time-feature analysis based on a wide range of different distributions.