mlss-2019 / tutorialsLinks
☆275Updated 5 years ago
Alternatives and similar repositories for tutorials
Users that are interested in tutorials are comparing it to the libraries listed below
Sorting:
- ☆260Updated 6 years ago
- Mathematics of Deep Learning, Courant Insititute, Spring 19☆278Updated 6 years ago
- Collection of probabilistic models and inference algorithms☆241Updated 5 years ago
- Implementing Bayes by Backprop☆184Updated 6 years ago
- Materials of the Nordic Probabilistic AI School 2019.☆130Updated 5 years ago
- repository with the lectures for MLSS Skoltech☆139Updated 5 years ago
- MLSS2019 Tutorial on Bayesian Deep Learning☆93Updated 5 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆95Updated 2 years ago
- Materials for Bayesian Methods in Machine Learning Course☆89Updated 9 months ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆121Updated 5 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- Differentiable Optimization-Based Modeling for Machine Learning☆339Updated 5 years ago
- A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch☆389Updated last year
- Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18☆67Updated 6 years ago
- ☆197Updated last year
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- Understanding ML and deep learning through geometry☆157Updated 3 years ago
- ☆170Updated last year
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- ☆64Updated 7 years ago
- Lectures for INFO8004 Advanced Machine Learning, ULiège☆113Updated 4 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.☆416Updated 4 years ago
- ☆123Updated 6 years ago
- Practical sessions for the Optimal Transport and Machine learning course at DS3 2018☆90Updated 7 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 5 years ago
- repository with the tutorials for MLSS Skoltech☆66Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- The collection of recent papers about variational inference☆85Updated 5 years ago