jackiddd

Adaptive-Soft-Sensor-Design

Github repo for the research paper titled "Integrating Adaptive Moving Window and Just-in-Time Learning Paradigms for Soft-Sensor Design"

DCGAN-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

denoising-diffusion-pytorch

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

keras

Deep Learning for humans

LeNet-5-Tensorflow

Object oriented Tensorflow implementation of the famous LeNet5 network by Yann Lecun.

LTDA

Code for 《Learning from Large-Scale Foundation Models: Enhanced Few-Shot Steel Defect Recognition》

ML-Tutorial-Experiment

Coding the Machine Learning Tutorial for Learning to Learn

nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

pytorch-MNIST-CelebA-cGAN-cDCGAN

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

RA-GAN

jackiddd/RA-GAN

jackiddd/Adaptive-Soft-Sensor-Design

Github repo for the research paper titled "Integrating Adaptive Moving Window and Just-in-Time Learning Paradigms for Soft-Sensor Design"

jackiddd/DCGAN-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

jackiddd/denoising-diffusion-pytorch

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

jackiddd/keras

Deep Learning for humans

jackiddd/LeNet-5-Tensorflow

Object oriented Tensorflow implementation of the famous LeNet5 network by Yann Lecun.

jackiddd/LTDA

Code for 《Learning from Large-Scale Foundation Models: Enhanced Few-Shot Steel Defect Recognition》

jackiddd/ML-Tutorial-Experiment

Coding the Machine Learning Tutorial for Learning to Learn

jackiddd/nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

jackiddd/pytorch-MNIST-CelebA-cGAN-cDCGAN

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

jackiddd/SCAEG

A Semantic Controllable Adversarial example Generation Method Based on Disentangled Representation

jackiddd/semi-supervised-GAN

There is the semi-supervised implement of 'Improved Techniques for Training GANs '

jackiddd/Semi-Supervised-Learning-GAN

Semi-supervised Learning GAN

jackiddd/shap

A game theoretic approach to explain the output of any machine learning model.

jackiddd/SSGAN-Tensorflow

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).

jackiddd/ssl_bad_gan

Good Semi-Supervised Learning That Requires a Bad GAN

jackiddd/stacked-autoencoder-pytorch

Stacked denoising convolutional autoencoder written in Pytorch for some experiments.

jackiddd/tensorflow-MNIST-cGAN-cDCGAN

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

jackiddd/ZJU-Clock-In

浙江大学健康打卡