dmelis

dmelis's Stars

• papers-we-love/papers-we-love

  Papers from the computer science community to read and discuss.

  Language:Shell89.1k3.1k2435.8k

• shap/shap

  A game theoretic approach to explain the output of any machine learning model.

  Language:Jupyter Notebook23.1k2452.6k3.3k

• eriklindernoren/PyTorch-GAN

  PyTorch implementations of Generative Adversarial Networks.

  Language:Python16.6k2191574.1k

• fossasia/visdom

  A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

  Language:Python10.1k1855611.1k

• utkuozbulak/pytorch-cnn-visualizations

  Pytorch implementation of convolutional neural network visualization techniques

  Language:Python7.9k1151061.5k

• wiseodd/generative-models

  Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

  Language:Python7.4k297662k

• PythonOT/POT

  POT : Python Optimal Transport

  Language:Python2.5k47257505

• geoopt/geoopt

  Riemannian Adaptive Optimization Methods with pytorch optim

  Language:Python868198981

• marcotcr/anchor

  Code for "High-Precision Model-Agnostic Explanations" paper

  Language:Jupyter Notebook7992876114

• artetxem/vecmap

  A framework to learn cross-lingual word embedding mappings

  Language:Python6482833131

• mathematical-tours/mathematical-tours.github.io

  Site web of the Mathematical Tours

  Language:TeX49331294

• HazyResearch/hyperbolics

  Hyperbolic Embeddings

  Language:Python378291264

• interpretable-ml/iml

  Interpretable ML package designed to explain any machine learning model.

  Language:JavaScript61857

• daniellevy/fast-dro

  PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets

  Language:Python58419

• bunnech/gwgan

  Learning Generative Models across Incomparable Spaces (ICML 2019)

  Language:Python26034

• melissawm/skprocrustes

  scikit-procrustes, a collection of solvers for the (Weighted) Orthogonal Procrustes Problem

  Language:Jupyter Notebook114303