Pinned Repositories
Deep-Learning-with-Keras
Code repository for Deep Learning with Keras published by Packt
framing-unet
## Quick and naive implementation of framing U-net paper in Keras (tf backend)
gan_tutorial
GAN and WGAN tutorial codes
GANs
a brief survey and implementations of generative adversarial nets(in progress)
Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
RNN-implementation-using-Numpy-binary-digit-addition
RNN implementation using only Numpy. Try to learn binary digit addition.
shallow-DANN-two-moon-dataset
Implementation: shallow Domain Adaptation Neural Network (DANN) with two moon dataset / % reference : https://arxiv.org/pdf/1505.07818v4.pdf
TDDIP
Time-Dependent Deep Image Prior for Dynamic MRI
tf-dann-py35
Tensorflow-gpu (1.0.0.rc2, Window, py35) implementation of Domain Adversarial Neural Network
wct2_trainer
I am not sure this was the final version for training the wave encoder and decoder that I used for the paper, but this is what I can find for now.
jaejun-yoo's Repositories
jaejun-yoo/TDDIP
Time-Dependent Deep Image Prior for Dynamic MRI
jaejun-yoo/wct2_trainer
I am not sure this was the final version for training the wave encoder and decoder that I used for the paper, but this is what I can find for now.
jaejun-yoo/gan_tutorial
GAN and WGAN tutorial codes
jaejun-yoo/Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
jaejun-yoo/ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
jaejun-yoo/numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
jaejun-yoo/PI-REC
:fire: PI-REC: Progressive Image Reconstruction Network With Edge and Color Domain. :fire: 图像翻译，条件GAN，AI绘画
jaejun-yoo/aahq-dataset
Artstation-Artistic-face-HQ Dataset (AAHQ)
jaejun-yoo/aqm-plus
PyTorch code for Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation (AQM+)
jaejun-yoo/deepul
jaejun-yoo/edge-connect
EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212
jaejun-yoo/fourier
An Interactive Introduction to Fourier Transforms
jaejun-yoo/generative-evaluation-prdc
Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
jaejun-yoo/GMLR
Generative Models for Low Rank Video Representation and Reconstruction
jaejun-yoo/how-to-read-pytorch
Quick, visual, principled introduction to pytorch code through five colab notebooks.
jaejun-yoo/manim
Animation engine for explanatory math videos
jaejun-yoo/Multi-Kernel-Regression-gTV-
The accompanying codes of the paper "Multi-Kernel Regression with Sparsity Constraint"
jaejun-yoo/neural-function-distributions
Pytorch implementation of Generative Models as Distributions of Functions 🌿
jaejun-yoo/Notebooks_for_SS
Jupyter notebooks to help the students understand complex math concepts of the signals and systems course.
jaejun-yoo/precision_recall
Based on "Improved precision and recall metric for assessing generative models"
jaejun-yoo/predictive-filter-flow
Predictive Filter Flow for fully/self-supervised learning on various vision tasks
jaejun-yoo/RL-Restore
Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning (CVPR 2018 Spotlight)
jaejun-yoo/SC-FEGAN
SC-FEGAN : Face Editing Generative Adversarial Network with User's Sketch and Color
jaejun-yoo/SinGAN
Pytorch implementation of "SinGAN: Learning a Generative Model from a Single Natural Image"
jaejun-yoo/Single-Image-Super-Resolution
A collection of high-impact and state-of-the-art SR methods
jaejun-yoo/SpiralSToRM
jaejun-yoo/ssbcnn
jaejun-yoo/TopPR
NeurIPS 2023 - TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models Official Code
jaejun-yoo/torchgpipe
A GPipe implementation in PyTorch
jaejun-yoo/WCT2
Software that can perform photorealistic style transfer without the need of any post-processing steps.