epfml / opt-summerschool
Short Course on Optimization for Machine Learning - Slides and Practical Labs - DS3 Data Science Summer School, June 24 to 28, 2019, Paris, France
☆20Updated 5 years ago
Alternatives and similar repositories for opt-summerschool:
Users that are interested in opt-summerschool are comparing it to the libraries listed below
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Short Course on Optimization for Machine Learning - Slides and Practical Lab - Pre-doc Summer School on Learning Systems, July 3 to 7, 20…☆18Updated 7 years ago
- Materials for ORIE 7191: Topics in Optimization for Machine Learning☆44Updated 6 years ago
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 7 years ago
- Repository with all material for SMILES, the Summer School of Machine Learning at Skoltech, taking place from the 16th to the 21st of Aug…☆55Updated 4 years ago
- ☆51Updated 9 months ago
- ☆16Updated 6 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- ☆53Updated 9 months ago
- ☆37Updated 3 years ago
- ☆30Updated 2 years ago
- ☆26Updated 6 years ago
- Materials for short course on Bayesian inference at the Data Science Summer School☆13Updated 5 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 8 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- Auxiliary variable Markov chain Monte Carlo methods☆10Updated 7 years ago
- ☆59Updated 6 years ago
- ☆26Updated 6 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆185Updated last year
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"☆10Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Determinantal Point Processes in Julia☆12Updated 5 years ago
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆26Updated 4 years ago
- Optimizing PAC-Bayes bounds for Stochastic Neural Networks with Gaussian weights☆27Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"☆16Updated 5 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago