Soheil Kolouri's Projects
A beautiful, simple, clean, and responsive Jekyll theme for academics
These slides were presented in BAMC 2019
Cumulative Distribution Transform
Code for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR 2019)
A toolkit for developing and comparing reinforcement learning algorithms.
Deeplab-resnet-101 in Pytorch with Jaccard loss
The Linear Optimal Transport Framework
Optimal transport transforms
Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Pure Numpy Implementation of the Coherent Point Drift Algorithm
PyTorch implementation of "Metric Learning with Adaptive Density Discrimination"
Radon Cumulative Distribution Transform
Pytorch implementation of set transformer
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Implementation of the Sliced Wasserstein Autoencoders
Sliced Wasserstein Distance for Learning Gaussian Mixture Models
TopoTrans: Optimal Transport meets Topological Data Analysis
The project webpage for Wasserstein Embedding for Graph Learning (WEGL)