duke-mlss / Duke-MLWS-2019Links
Duke Machine Learning Winter School 2019
☆26Updated 6 years ago
Alternatives and similar repositories for Duke-MLWS-2019
Users that are interested in Duke-MLWS-2019 are comparing it to the libraries listed below
Sorting:
- Parametric Gaussian Process Regression for Big Data (Matlab Version)☆24Updated 7 years ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- This implementation of DeePyMoD is no longer maintained! We switched to a PyTorch based implementation: https://github.com/PhIMaL/DeePyM…☆24Updated 5 years ago
- ☆21Updated 7 years ago
- A Discussion on Solving Partial Differential Equations using Neural Networks☆66Updated 6 years ago
- Deep Learning application to the partial differential equations☆30Updated 7 years ago
- PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.☆98Updated 3 years ago
- TensorFlow Probability Tutorial☆37Updated 5 years ago
- A tutorial for students that surveys basic ML techniques in ipython notebook format.☆27Updated 6 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Gaussian Process and Uncertainty Quantification Summer School 2018☆31Updated 2 years ago
- ☆14Updated 6 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 5 years ago
- UNIVR PDE course project and just for fun☆116Updated 8 years ago
- ☆30Updated 3 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆95Updated 2 years ago
- The Incredible TensorFlow 2: a curated list of tutorials, papers, projects, communities and more relating to TensorFlow 2.☆30Updated 6 years ago
- Course notes for graduate-level class on numerical methods for deep learning☆51Updated 4 years ago
- ☆73Updated 6 years ago
- Bayesian calibration using Tensorflow Probability☆35Updated 6 years ago
- A hands-on tutorial on supervised learning with Gaussian processes☆37Updated 5 years ago
- ☆28Updated 6 years ago
- Distributed Training of Bayesian Neural Networks at Scale☆11Updated 5 years ago
- Book: Practical Probabilistic Machine Learning in Python☆10Updated 4 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- ☆41Updated 6 years ago
- Deep Learning of Turbulent Scalar Mixing☆17Updated 6 years ago
- Talks from Neil Lawrence☆54Updated last year
- A pyTorch Extension for Applied Mathematics☆40Updated 5 years ago