Julien Guillaumin (JGuillaumin)

JGuillaumin

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Location:France, Paris

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Julien Guillaumin's starred repositories

todomvc-vue-composition-api

TodoMVC built with Vue 3 Composition Api and Vuex

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StyleGAN2-Tensorflow-2.0

StyleGAN 2 in Tensorflow 2.0

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aistore

AIStore: scalable storage for AI applications

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OpenChem

OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research

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Self-Balanced-Dropout

A modified dropout which can reduce the co-adaptation problem.

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stylegan

StyleGAN - Official TensorFlow Implementation

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SizeLoss_WSS

Code of our MIDL 2018 paper and MedIA extension: https://arxiv.org/abs/1805.04628

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Switchable-Normalization

Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779

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abseil-py

Abseil Common Libraries (Python)

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meeting-cpp-2017

Slides and code for my talk at MeetingC++ 2017

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tan

Code for the paper "Transductive Adversarial Networks (TAN)" by Sean Rowan (2018).

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Photo-Realistic-Super-Resoluton

Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

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Deep-learning-with-cats

Deep learning with cats (^._.^)

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ironcar

🏎️ Mini self-driving car for {curious, passionnate} people.

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ironcar

Mini self-driving car for {curious, passionnate} people.

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tensorflow-on-raspberry-pi

TensorFlow for Raspberry Pi

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meetup-cfp

Meetup Call for Paper pour soumettre vos idées de sujets

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NeuralNetwork

Toy Neural Network in Python, to learn the basic concepts and see it at work. The neural network tries to reproduce a picture given in input.

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Awesome-GANs

Awesome Generative Adversarial Networks with tensorflow

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tensorflow-workshop

Slides and code from our TensorFlow workshop.

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tftables

HDF5 interface for Tensorflow.

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dynamic_sampled_softmax_loss

A new TensorFlow op that calculates sampled softmax loss with dynamic number of true classes per training instance.

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tensorflow-cpp-op-example

Simple example of implementing a new Tensorflow operation and its gradient in C++.

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