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Stars: ✭ 30 (-36.17%)
Mutual labels:  generative-adversarial-network, self-driving-car
gan-qp.pytorch
Unofficial PyTorch implementation of "GAN-QP: A Novel GAN Framework without Gradient Vanishing and Lipschitz Constraint"
Stars: ✭ 26 (-44.68%)
Mutual labels:  generative-adversarial-network
seqgan-music
Implementation of a paper "Polyphonic Music Generation with Sequence Generative Adversarial Networks" in TensorFlow
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Mutual labels:  generative-adversarial-network
AvatarGAN
Generate Cartoon Images using Generative Adversarial Network
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Mutual labels:  generative-adversarial-network
steam-stylegan2
Train a StyleGAN2 model on Colaboratory to generate Steam banners.
Stars: ✭ 30 (-36.17%)
Mutual labels:  generative-adversarial-network
gans-collection.torch
Torch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)
Stars: ✭ 53 (+12.77%)
Mutual labels:  generative-adversarial-network
GAN-auto-write
Generative Adversarial Network that learns to generate handwritten digits. (Learning Purposes)
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Mutual labels:  generative-adversarial-network
ADL2019
Applied Deep Learning (2019 Spring) @ NTU
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Mutual labels:  generative-adversarial-network
dukes
Self Driving RC Car
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Mutual labels:  self-driving-car
GTAV-Self-driving-car
Self driving car in GTAV with Deep Learning
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Mutual labels:  self-driving-car
CsiGAN
An implementation for our paper: CsiGAN: Robust Channel State Information-based Activity Recognition with GANs (IEEE Internet of Things Journal, 2019), which is the semi-supervised Generative Adversarial Network (GAN) for Channel State Information (CSI) -based activity recognition.
Stars: ✭ 23 (-51.06%)
Mutual labels:  generative-adversarial-network
hgail
gail, infogail, hierarchical gail implementations
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Mutual labels:  generative-adversarial-network
domain adapt
Domain adaptation networks for digit recognitioning
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Mutual labels:  generative-adversarial-network
lagvae
Lagrangian VAE
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Mutual labels:  generative-adversarial-network
OgmaDrive
Ogma - OgmaDrive https://ogma.ai/
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BtcDet
Behind the Curtain: Learning Occluded Shapes for 3D Object Detection
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Deep-Exemplar-based-Video-Colorization
The source code of CVPR 2019 paper "Deep Exemplar-based Video Colorization".
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Mutual labels:  generative-adversarial-network
gan-weightnorm-resnet
Generative Adversarial Network with Weight Normalization + ResNet
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Mutual labels:  generative-adversarial-network
self-driving-car-nd
Udacity's Self-Driving Car Nanodegree project files and notes.
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Mutual labels:  self-driving-car
Deep-Learning
It contains the coursework and the practice I have done while learning Deep Learning.🚀 👨‍💻💥 🚩🌈
Stars: ✭ 21 (-55.32%)
Mutual labels:  generative-adversarial-network

projects

minimum viable experiment series

Like single file experiments to trully grok things? I got you with Reinforcement Learning and Evolution Stratagies tutorials.

generative models and unsupervised learning for videos

I wrote Recurrent Winner-Take-All and Perception Updating Networks. Those methods show how to learn features by exploiting temporal context and to predict future frames in a video (think video compressor or robot planning).

subpixel


Enhance! A neural network for image superresolution. This project hit the front page of Hacker News and Trending on Github.

pymerkletools

I love bitcoin and blockchain! I wrote Tierion's pymerkletools for creating Merkle trees, generating merkle proofs, and verification of merkle proofs.

learning a driving simulator

I trained generative adversarial and recurrent neural networks to simulate highway videos.

self coloring books

A segmentation network for self driving car data pipeline

deep learning for self-driving cars

CNN+RNN model for deciding where the car should go during Summer at comma.ai

EEG analysis for Brain Machine Interface

I wrote the CSP pipeline for EEG analysis in Theano and fine-tuned everything end-to-end. I could've won BCI competition 2 T_T

Information Theoretic Learning Autoencoders

I want to use deep information theoretic learning to compress and make images look pretty.

RGB-D object recognition

I trained convnets to recognize objects in 3D when interning with Paracosm.io

ECG analysis

My undergrad and master research was on blind source extraction. We had ECG recordings from a pregnant woman and we had to separate the ECG signal of the fetus from the signal of the woman. I used kernels methods back then. You kids don't know that anymore, but kernels used to be cool.

Keras contributor


Keras' community is awesome! I contribute with both Tensorflow and Theano code to the source. Some advanced contributions include Neural Turing Machines and Spatial Transformer Networks.

Hubot Recognizer

I put some deep learning on Slack

deep learning with python

video course about deep learning. Mostly using Keras and Theano.

publications

papers, in the end of the day I write machine learning papers for a living

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