epfl-lasa / ML_toolbox
A Machine learning toolbox containing algorithms for non-linear dimensionality reduction, clustering, classification and regression along with examples and tutorials which accompany the Master level "Advanced Machine Learning" and "Machine Learning Programming" courses taught at EPFL by Prof. Aude Billard
☆96Updated 4 years ago
Alternatives and similar repositories for ML_toolbox:
Users that are interested in ML_toolbox are comparing it to the libraries listed below
- learning task trajectories using Probabilistic Movement Primitives☆12Updated 7 years ago
- Task Parameterized Gaussian Mixture Model (TP-GMM) and Regression implemented purely on numpy☆30Updated 5 years ago
- Learning stable nonlinear dynamics and attractors with linear parameter varying systems☆14Updated 7 years ago
- Stabilizable Nonlinear Dynamics Learning☆21Updated 5 years ago
- Gaussian Mixture Model (GMM) and Gaussian Mixture Regression (GMR) implemented purely on numpy☆62Updated 5 years ago
- Set of exercises accompanying the ICRA 2019 Tutorial on Dynamical System based Learning from Demonstration: https://epfl-lasa.github.io/T…☆62Updated 4 years ago
- Learning second order dynamical system☆10Updated 5 years ago
- Great resources for learning optimal control☆17Updated 5 years ago
- Dynamical Movement Primitives in Python☆9Updated 7 years ago
- Toolbox including several techniques for estimation of Globally Asymptotically Stable Dynamical Systems from demonstrations. It focuses o…☆32Updated 2 years ago
- LfD: Learning from Demonstrations for Robotic Manipulation☆47Updated 9 years ago
- python library to generate and learn collision-free movement using differential and Riemannian geometry☆12Updated last year
- Matlab source code for the SONIG algorithm: Sparse Online Noisy-Input Gaussian process regression.☆28Updated 7 years ago
- This repository contains code and information for the computer exercises for the tutorial on Learning from Demonstration at ICRA 2016.☆44Updated 8 years ago
- Nonparametric Bayesian Inference for Sequential Data. Includes state-of-the-art MCMC inference for Beta process Hidden Markov Models (BP…☆79Updated 6 years ago
- ☆21Updated 3 years ago
- Dynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long bee…☆49Updated 10 months ago
- Dynamic Movement Primitives in Python☆14Updated last year
- Optimal Control for Robotics -- Tufts University -- ME 149 -- Spring 2018☆51Updated 6 years ago
- Gaussian Process Model Dynamic System Identification Toolbox for Matlab☆90Updated 7 years ago
- Learning visual servoing with deep features and fitted Q-iteration☆33Updated 7 years ago
- Input Inference for Control (i2c), a control-as-inference framework for optimal control☆23Updated last year
- A set of Matlab/Octave files that performs a method of Nonlinear System Identification.☆23Updated 6 years ago
- 3R Robot Inverse Kinematics with ANFIS, RBF and ANN using Matlab 2019b☆11Updated 4 years ago
- Hado van Hasselt's Reinforcement Learning Code☆10Updated 7 years ago
- Gaussian Mixture Regression☆177Updated last month
- Implementation of the paper "Movement Primitives via Optimization" (Dragan et al., 2016). It includes both the adaptation of trajectories…☆21Updated 6 years ago
- Structured framework for learning mechanical systems in PyTorch☆24Updated 5 years ago
- Behavior Optimization and Learning for Robots☆65Updated 2 months ago
- A curated list of neural applications in control theory and practice☆58Updated 7 years ago