daniellutscher

artemis

Artemis aims to get rid of all the boring, bureaucratic coding (plotting, file management, organizing experiments, etc) involved in machine learning projects, so you can get to the good stuff quickly.

awesome-deep-learning-papers

The most cited deep learning papers

awesome-rl

Reinforcement learning resources curated

awesome-tensorflow

TensorFlow - A curated list of dedicated resources http://tensorflow.org

colossus

Colossus — An example microservice architecture for Kubernetes using Bazel, Go, Java, Docker, Kubernetes, Minikube, Gazelle, gRPC, Prometheus, Grafana, and more

EfficientNet-PyTorch

A PyTorch implementation of EfficientNet

MCDC

Code for the research paper: Mixing Consistent Deep Clustering

MixMatch-TransferLearning

Combines the SSL Method MixMatch with a pre-trained model (EfficientNet) on a chest x-ray dataset.

NSGA-II

an implementation of NSGA-II in java

PyRiemann

Python implementation for computation in Riemannian geometry, using OpenBLAS

daniellutscher/MixMatch-TransferLearning

Combines the SSL Method MixMatch with a pre-trained model (EfficientNet) on a chest x-ray dataset.

daniellutscher/artemis

Artemis aims to get rid of all the boring, bureaucratic coding (plotting, file management, organizing experiments, etc) involved in machine learning projects, so you can get to the good stuff quickly.

daniellutscher/awesome-deep-learning-papers

The most cited deep learning papers

daniellutscher/awesome-rl

Reinforcement learning resources curated

daniellutscher/awesome-tensorflow

TensorFlow - A curated list of dedicated resources http://tensorflow.org

daniellutscher/colossus

Colossus — An example microservice architecture for Kubernetes using Bazel, Go, Java, Docker, Kubernetes, Minikube, Gazelle, gRPC, Prometheus, Grafana, and more

daniellutscher/EfficientNet-PyTorch

A PyTorch implementation of EfficientNet

daniellutscher/MCDC

Code for the research paper: Mixing Consistent Deep Clustering

daniellutscher/NSGA-II

an implementation of NSGA-II in java

daniellutscher/PyRiemann

Python implementation for computation in Riemannian geometry, using OpenBLAS

daniellutscher/catalyst

Reproducible and fast DL & RL.

daniellutscher/cookiecutter-git

Git repo project template using Cookiecutter :cookie:

daniellutscher/DCC

This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper

daniellutscher/DeepRL

Modularized Implementation of Deep RL Algorithms in PyTorch

daniellutscher/ICT

daniellutscher/medical-imaging-datasets

A list of Medical imaging datasets.

daniellutscher/MixMatch-pytorch

Code for "MixMatch - A Holistic Approach to Semi-Supervised Learning"

daniellutscher/pipeline

PipelineAI Kubeflow Distribution

daniellutscher/pymc3

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano

daniellutscher/Skin-cancer-image-classification

Skin cancer classification using Inceptionv3

daniellutscher/tensorflow

An Open Source Machine Learning Framework for Everyone

daniellutscher/tensorflow-models

Models built with TensorFlow

daniellutscher/Tensorflow-Project-Template

A best practice for tensorflow project template architecture.

daniellutscher/UnsupervisedDeepLearning-Pytorch

This repository tries to provide unsupervised deep learning models with Pytorch

daniellutscher/VaDE

Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering

daniellutscher/VAE-for-Image-Generation

Variational AutoEncoder - Keras implementation on mnist and cifar10 datasets

daniellutscher/variational-autoencoder

Variational autoencoder implementation using Tensorflow and Python

daniellutscher/vincentherrmann.github.io

:triangular_ruler: A flexible two-column Jekyll theme. Perfect for personal sites, blogs, and portfolios hosted on GitHub or your own server.