mackelab / machine-learning-I
Slides and lecture notes for the course 'machine learning I' taught at the Graduate School Neural Information Processing in Tuebingen.
☆31Updated 9 years ago
Alternatives and similar repositories for machine-learning-I:
Users that are interested in machine-learning-I are comparing it to the libraries listed below
- Python 3.7 version of David Barber's MATLAB BRMLtoolbox☆24Updated 6 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18☆64Updated 6 years ago
- ☆64Updated 6 years ago
- Experiments in Bayesian Machine Learning☆69Updated 5 years ago
- Sandbox for generating visualizations of the bias-variance tradeoff for Machine Learning at Berkeley's blog.☆14Updated 7 years ago
- Scalable GP Adapter for Time Series Classification☆13Updated 7 years ago
- ☆30Updated 4 years ago
- Contains all materials for the paper "A counterfactual simulation model of causal judgment".☆23Updated 3 years ago
- Materials for Bayesian Methods in Machine Learning Course☆88Updated 3 months ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 8 years ago
- Self-study notes for Indian Buffet Process, from reading through "The Indian Buffet Process: An Introduction and Review", Griffiths, Ghah…☆11Updated 8 years ago
- Hidden Markov Models (HMMs) with tied states and autoregressive observations☆23Updated 4 years ago
- A Random Matrix Approach to Extreme Learning Machine☆14Updated 7 years ago
- ☆31Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Material for my Caltech tutorial on deep learning and tensor methods☆70Updated 6 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 6 years ago
- ☆25Updated 2 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Course Repository for CS 375 (Large Scale Neural Network Modules for Neuroscience)☆39Updated 3 weeks ago
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 5 years ago
- A deep generative model of semi-unsupervised learning☆15Updated 6 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Lectures for INFO8004 Advanced Machine Learning, ULiège☆108Updated 2 weeks ago
- Code for our AAMAS 2020 paper: "A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry".☆26Updated last year
- Gaussian Process and Uncertainty Quantification Summer School 2017☆26Updated 2 years ago
- Implementation of linear CorEx and temporal CorEx.☆37Updated 3 years ago
- ☆59Updated 6 years ago
- Notebooks explaining the intuition behind the Expectation Maximisation algorithm☆38Updated 5 years ago