There are 1 repository under robust-estimation topic.
Statsmodels: statistical modeling and econometrics in Python
Certifiable Outlier-Robust Geometric Perception
Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.
This library is an implementation of the algorithm described in Distributed Trajectory Estimation with Privacy and Communication Constraints: a Two-Stage Distributed Gauss-Seidel Approach.
Solve many kinds of least-squares and matrix-recovery problems
Robust estimations from distribution structures: Invariant moments.
Mean and Covariance Matrix Estimation under Heavy Tails
(ICML 2020) Message Passing Least Squares Algorithm for Rotation Averaging
This is an open source library that can be used to autofocus telescopes. It uses a novel algorithm based on robust statistics. For a preprint, see https://arxiv.org/abs/2201.12466 .The library is currently used in Astro Photography tool (APT) https://www.astrophotography.app/
Robust estimations from distribution structures: Central moments.
MATLAB demo for the paper "Non-smooth M-Estimator for Maximum Consensus Estimation"
A new take on EEG sleep spindles detection exploiting a generative model (dynamic bayesian network) to characterize reoccurring dynamical regimes of single-channel EEG.
A Robust Dynamic Multi-Modal Data Fusion Algorithm
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.