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janus - Optimized Recommending System Based on 'tensorflow'

Proposes a coarse-to-fine optimization of a recommending system based on deep-neural networks using 'tensorflow'.

Last updated

2.12 score 131 scripts 229 downloads

snap - Simple Neural Application

A simple wrapper to easily design vanilla deep neural networks using 'Tensorflow'/'Keras' backend for regression, classification and multi-label tasks, with some tweaks and tricks (skip shortcuts, embedding, feature selection and anomaly detection).

Last updated

2.00 score 5 scripts 207 downloads

sense - Automatic Stacked Ensemble for Regression Tasks

Stacked ensemble for regression tasks based on 'mlr3' framework with a pipeline for preprocessing numeric and factor features and hyper-parameter tuning using grid or random search.

Last updated

1.78 score 1 scripts 221 downloads

wired - Weighted Adaptive Prediction with Structured Dependence

Builds a joint probabilistic forecast across series and horizons using adaptive copulas (Gaussian/t) with shrinkage-repaired correlations. At the low level it calls a probabilistic mixer per series and horizon, which backtests several simple predictors, predicts next-window Continuous Ranked Probability Score (CRPS), and converts those scores into softmax weights to form a calibrated mixture (r/q/p/dfun). The mixer blends eight simple predictors: a naive predictor that wraps the last move in a PERT distribution; an arima predictor using auto.arima for one-step forecasts; an Exponentially Weighted Moving Average (EWMA) gaussian predictor with mean/variance under a Gaussian; a historical bootstrap predictor that resamples past horizon-aligned moves; a drift residual bootstrap predictor combining linear trend with bootstrapped residuals; a volatility-scaled naive predictor centering on the last move and scaling by recent volatility; a robust median mad predictor using median/MAD with Laplace or Normal shape; and a shrunk quantile predictor that fits a few quantile regressions over time and interpolates to a full predictive. The function then couples the per-series mixtures on a common transform (additive/multiplicative/log-multiplicative), simulates coherent draws, and returns both transformed- and level-scale samplers and summaries.

Last updated

1.76 score 29 scripts 470 downloads

proteus - Multiform Seq2Seq Model for Time-Feature Analysis

Seq2seq time-feature analysis based on variational model, with a wide range of distributions available for the latent variable.

Last updated

1.53 score 34 scripts 214 downloads

unfold - Mapping Hidden Geometry into Future Sequences

A variational mapping approach that reveals and expands future temporal dynamics from folded high-dimensional geometric distance spaces, unfold turns a set of time series into a 4D block of pairwise distances between reframed windows, learns a variational mapper that maps those distances to the next reframed window, and produces horizon-wise predictive functions for each input series. In short: it unfolds the future path of each series from a folded geometric distance representation.

Last updated

1.30 score 454 downloads

xpect - Probabilistic Time Series Forecasting with XGBoost and Conformal Inference

Implements a probabilistic approach to time series forecasting combining XGBoost regression with conformal inference methods. The package provides functionality for generating predictive distributions, evaluating uncertainty, and optimizing hyperparameters using Bayesian, coarse-to-fine, or random search strategies.

Last updated

1.30 score 1 stars 1 scripts 531 downloads

temper - Temporal Encoder-Masked Probabilistic Ensemble Regressor

Implements a probabilistic ensemble time-series forecaster that combines an auto-encoder with a neural decision forest whose split variables are learned through a differentiable feature-mask layer. Functions are written with 'torch' tensors and provide CRPS (Continuous Ranked Probability Scores) training plus mixture-distribution post-processing.

Last updated

1.30 score 71 downloads

hmix - Hidden Markov Model for Predicting Time Sequences with Mixture Sampling

An algorithm for time series analysis that leverages hidden Markov models, cluster analysis, and mixture distributions to segment data, detect patterns and predict future sequences.

Last updated

1.00 score 2 scripts 460 downloads

audrex - Automatic Dynamic Regression using Extreme Gradient Boosting

Dynamic regression for time series using Extreme Gradient Boosting with hyper-parameter tuning via Bayesian Optimization or Random Search.

Last updated

1.00 score 3 scripts 504 downloads

organik - Multi-Horizon Probabilistic Ensemble with Copulas for Time Series Forecasting

Trains per-horizon probabilistic ensembles from a univariate time series. It supports 'rpart', 'glmnet', and 'kNN' engines with flexible residual distributions and heteroscedastic scale models, weighting variants by calibration-aware scores. A Gaussian/t copula couples the marginals to simulate joint forecast paths, returning quantiles, means, and step increments across horizons.

Last updated

1.00 score 1 stars 142 downloads

spinner - An Implementation of Graph Net Architecture Based on 'torch'

Proposes a 'torch' implementation of Graph Net architecture allowing different options for message passing and feature embedding.

Last updated

1.00 score 8 scripts 191 downloads

dymo - Dynamic Mode Decomposition Forecasting with Conformal Predictive Sampling

The DYMO package provides tools for multi-feature time-series forecasting using a Dynamic Mode Decomposition (DMD) model combined with conformal predictive sampling for uncertainty quantification.

Last updated

1.00 score 3 scripts 158 downloads

segen - Sequence Generalization Through Similarity Network

Proposes an application for sequence prediction generalizing the similarity within the network of previous sequences.

Last updated

1.00 score 1 scripts 194 downloads

chopper - Changepoint-Aware Ensemble for Probabilistic Modeling

Implements a changepoint-aware ensemble forecasting algorithm that combines Theta, TBATS (Trigonometric, Box-Cox transformation, ARMA errors, Trend, Seasonal components), and ARFIMA (AutoRegressive, Fractionally Integrated, Moving Average) using a product-of-experts approach for robust probabilistic prediction.

Last updated

1.00 score 3 scripts 562 downloads

naive - Empirical Extrapolation of Time Feature Patterns

An application for the empirical extrapolation of time features selecting and summarizing the most relevant patterns in time sequences.

Last updated

1.00 score 184 downloads

codez - Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on Tensorflow

Proposes Seq2seq Time-Feature Analysis using an Encoder-Decoder to project into latent space and a Forward Network to predict the next sequence.

Last updated

1.00 score 1 scripts 226 downloads

jenga - Fast Extrapolation of Time Features using K-Nearest Neighbors

Fast extrapolation of univariate and multivariate time features using K-Nearest Neighbors. The compact set of hyper-parameters is tuned via grid or random search.

Last updated

1.00 score 164 downloads

spooky - Time Feature Extrapolation Using Spectral Analysis and Jack-Knife Resampling

Proposes application of spectral analysis and jack-knife resampling for multivariate sequence forecasting. The application allows for a fast random search in a compact space of hyper-parameters composed by Sequence Length and Jack-Knife Leave-N-Out.

Last updated

1.00 score 212 downloads

tetragon - Automatic Sequence Prediction by Expansion of the Distance Matrix

Each sequence is predicted by expanding the distance matrix. The compact set of hyper-parameters is tuned through random search.

Last updated

1.00 score 226 downloads

lambdaTS - Variational Seq2Seq Model with Lambda Transformer for Time Series Analysis

Time series analysis based on lambda transformer and variational seq2seq, built on 'Torch'.

Last updated

1.00 score 230 downloads