17 skills found
raphaelvallat / EntropyEntroPy: complexity of time-series in Python (DEPRECATED)
arthurpessa / OrdpyA Python package for data analysis with permutation entropy and ordinal network methods.
JuliaDynamics / ComplexityMeasures.jlEstimators for probabilities, entropies, and other complexity measures derived from data in the context of nonlinear dynamics and complex systems
ValentinaUn / Fast Permutation EntropyMATLAB script for efficiently computing values of permutation entropy from 1D time series in sliding windows
neurotrader888 / PermutationEntropyA simple python implementation of permutation entropy.
ValentinaUn / Ordinal Patterns Based AnalysisOrdinal-patterns-based analysis toolbox (permutation entropy, robust permutation entropy, conditional entropy of ordinal patterns, ordinal distributions)
usnistgov / PasswordMetricsPython code for 1) permuting randomly-generated passwords for easier entry on mobile devices, and 2) for estimating entropy lost as a result of said permutation.
amazingharry95 / EEG Seizure ClassificationThis is for my Biomedical Computation class in campus. The problem is for classifying EEG Dataset from Bonn University that contains seizure & non-seizure patients. Feature Extraction is using Weighted Permutation Entropy and for the classification method we are using Support Vector Machine. All codes are in Python 2.7 but it just for the feature extraction. The Classification technique is perform using RapidMiner Studio.
alberto-ara / Multivariate Multiscale Permutation EntropyApply multivariate multiscale permutation entropy transform to multivariate time series
JohnFabila / PEGThis function calculates permutation entropy for graphs (PEG).
brunorrboaretto / Chaos Detection ANNNeural network that has been trained to detect temporal correlation and distinguish chaotic from stochastic signals
hvribeiro / Knnpeknnpe: A Python package implementing the k-nearest neighbor permutation entropy
seb-berger / ZztopGNU Octave/MATLAB code supplementing the journal article "Permutation Entropy: Too Complex a Measure for EEG Time Series?" (Entropy 2017, 19, 692)
emulasion / Permutation EntropyFast evaluation of permutation entropy of a time series. A Python (NumPy) wrapper is included.
marisamohr / MpePyFunctions for computation of different types of multivariate permutation entropies for time series analysis
pietro-foini / ISI WFPMachine learning model to forecast food security indicators using historical data and external factors like macroeconomics, market prices, weather, and conflicts.
BenJ-cell / Differentiable Ranks And Sorting Using Optimal TransportSorting is a necessary tool for machine learning, to create algorithms (k-NN) or test-time metrics like top-k classification accuracy or losses based on the rank. Nevertheless it seems to be a difficult task for automatically differentiable pipelines in DL. Sorting gives us two vectors, this application is not differentiable as we are working with integer-valued permutation. In the paper they aim to implement a differentiable proxy of the basic approach. The article conceive this proxy by thinking of an optimal assignment problem. We sort n values by matching them to a probability measure supported on any increasing family of n target values. Therefore we are considering Optimal Transport (OT) as a relaxation of the basic problem allowing us to extend rank and sort operators using probability measures. The auxiliary measure will be supported on m increasing values with m $\ne$ n. Introducing regularization with an entropic penalty and applying Sinkhorn iterations will allow to gain back differentiable operators. The smooth approximation of rank and sort allow to use the 0/1 loss and the quantile regression loss.
