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deconvolution-microscopy-cyclegan

CycleGAN with a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry

deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

deep_gaussian_process_project

Project on Deep Gaussian processes for the MVA course "Bayesian Machine Learning"

deep_learning_for_scientific_computing

Repository for the development of the projects for the Deep Learning for Scientific Computing course taught by Professor Mishra at ETH Zürich in the spring semester 2021

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

deeplmva

Mini-Projects for the course "Deep Learning" at MVA

demos

Demos and tutorials for ORIE 4741

dendritic_ot

Optimal Transport and barycenters for dendritic measures

diploma

A mathematical model for choosing the optimal transport network route. Based on NBA* method

dirichlet-process

Implementation of the dirichlet process for multivariate clustering

discrete-inference-project

Code for the project in the Discrete Inference class

dissertation_scripts

R Scripts used for my dissertation : "Modelling and analysis of social network data from rank preferences"

distance-between-datasets-via-optimal-transport

Formulate an approach via Optimal Transport Theory that provides a robust comparison of datasets, defined on both the same and different topological space that correlates well within the domain adaptation and task similarity context.

distributed-frank-wolfe

A PySpark Implementation of "Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm".

dllr

deep learning low rank

drl-optimization

An Exploration of Optimization Alternatives for Deep Reinforcement Learning (Deep Learning 2018, ETH Zurich)

drot

Dual Regularized Optimal Transport

ds220

Independent Study for Graph Database using Neo4J

ds440

dsw

Distributional Sliced-Wasserstein distance code

dt

Dold-Thom, Homology and Optimal Transport.

dynamic-ot

Finite element discretization of dynamical optimal transport using Firedrake. This repo contains the code from the paper: A. Natale, and G. Todeschi. "A mixed finite element discretization of dynamical optimal transport." arXiv preprint arXiv:2003.04558 (2020).

ecml2018-featureselectionoptimaltransport

ee227c.github.io

EE227C (Spring 2018) Course page

emacs-ipython-notebook

IPython 2.x/3.x notebook client in Emacs

epsilon

A general convex solver based on functions with efficient proximal operators.

errp_bcifes

The codes that detect error feedback when the participants receive visual or somato-sensory feedback . The methodology implements optimal transport to transport source data samples within the distribution of the target data samples. This allows for cross-subject training and hence, does not require re-training for new participants or sessions.

esrnn-gpu

PyTorch GPU implementation of the ES-RNN model for time series forecasting

eth-dl-cheat-sheet

Cheat sheet for the "Deep Learning" course at ETH Zürich

eth-machinelearning-projects

These projects were part of the Introduction to Machine Learning course at ETH Zürich.