cc-skuehn / Manifold_Learning
Worked examples about manifold learning using sklearn and jupyter
☆51Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for Manifold_Learning
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Preconditioned ICA for Real Data☆107Updated last week
- Python 3.7 version of David Barber's MATLAB BRMLtoolbox☆24Updated 6 years ago
- Variational Fourier Features☆83Updated 3 years ago
- Embed strange attractors using a regularizer for autoencoders☆131Updated 3 years ago
- ☆28Updated 5 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 5 years ago
- Foundational library for Kernel methods in pattern analysis and machine learning☆41Updated last year
- TensorFlow Probability Tutorial☆36Updated 5 years ago
- Several maximum likelihood ICA algorithms, including Picard☆22Updated 7 years ago
- Online Robust Principal Component Analysis☆93Updated 4 years ago
- ☆63Updated 6 years ago
- Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead☆72Updated 4 years ago
- Open source library for combining TDA and Machine Learning☆89Updated last year
- An algorithm for unsupervised discovery of sequential structure☆25Updated 6 years ago
- Dynamical Components Analysis☆30Updated last year
- Convolution dictionary learning for time-series☆121Updated last month
- Code for Hidden Markov Nonlinear ICA☆23Updated 3 years ago
- Implementation of linear CorEx and temporal CorEx.☆36Updated 3 years ago
- Recursive Self-Organizing Map/Neural Gas.☆52Updated last year
- Multi-task regression in Python☆26Updated 3 years ago
- Time-Contrastive Learning☆64Updated 6 years ago
- Tensorflow 2.0 implementation of Adversarial Autoencoders☆20Updated 5 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 6 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Implementaion of Gaussian Process Recurrent Neural Networks developed in "Neural Dynamics Discovery via Gaussian Process Recurrent Neura…☆40Updated last year
- ☆65Updated 3 months ago
- Practical sessions for the Optimal Transport and Machine learning course at DS3 2018☆86Updated 6 years ago
- python code for kernel methods☆38Updated 5 years ago
- Experiments on Self-Supervised Learning on EEG data☆18Updated 4 years ago