joanbruna / MathsDL-spring19Links
Mathematics of Deep Learning, Courant Insititute, Spring 19
☆276Updated 6 years ago
Alternatives and similar repositories for MathsDL-spring19
Users that are interested in MathsDL-spring19 are comparing it to the libraries listed below
Sorting:
- Topics course Mathematics of Deep Learning, NYU, Spring 18☆544Updated 2 years ago
- Personal and biased selection of ML resources☆150Updated 5 years ago
- Understanding normalizing flows☆132Updated 5 years ago
- MLSS2019 Tutorial on Bayesian Deep Learning☆91Updated 5 years ago
- ☆274Updated 4 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Differentiable Optimization-Based Modeling for Machine Learning☆336Updated 5 years ago
- Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18☆66Updated 6 years ago
- Code and assignment repository for the Imperial College Mathematics department Deep Learning course☆263Updated 6 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆95Updated 2 years ago
- Deep learning course CE7454, 2019☆190Updated 5 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆185Updated last year
- Understanding ML and deep learning through geometry☆157Updated 3 years ago
- ICLR Reproducibility Challenge 2019☆218Updated 6 years ago
- Implementing Bayes by Backprop☆184Updated 6 years ago
- Collection of probabilistic models and inference algorithms☆241Updated 5 years ago
- ☆260Updated 5 years ago
- Basic experiment framework for tensorflow.☆92Updated 3 years ago
- Collaborative lecture notes for Spring '19 NYU DL class☆119Updated 5 years ago
- Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"☆127Updated 6 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- ☆167Updated 10 months ago
- ☆123Updated 6 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- ☆196Updated 10 months ago
- EE227C (Spring 2018) Course page☆224Updated 4 years ago
- A curated list of resources dedicated to bayesian deep learning☆415Updated 8 years ago
- ☆241Updated 2 years ago
- Code for paper: "Support Vector Machines, Wasserstein's distance and gradient-penalty GANs maximize a margin"☆178Updated 5 years ago