imwildstone's repositories
Achievement_prediction
通过MLP和LSTM分析大学生平日的各种行为信息是否与成绩有足够的影响
AnoGAN-WGAN-pytorch
WGAN based AnoGAN
CAN_GAN_Anomaly
Paper "CAN Bus Intrusion Detection based on Auxiliary Classifier GAN and Out-of-Distribution Detection" Code
darts
A python library for easy manipulation and forecasting of time series.
dock-substrate
Substrate node for Dock blockchain
examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
f-AnoGAN-1
Implementation of f-AnoGAN with PyTorch
fast_adversarial
[ICLR 2020] A repository for extremely fast adversarial training using FGSM
FGSM-1
使用pytorch实现FGSM
ganomaly
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
ipfs-desktop
An unobtrusive and user-friendly desktop application for IPFS on Windows, Mac and Linux.
MaskingvsReconstruction
In this project, we present a comparative analysis between reconstruction based techniques (AutoEncoders and its variants) and masking based techniques (such as BERT) for in-vehicle intrusion detection.
MobileOne
An Improved One millisecond Mobile Backbone
PaperRobot
Code for PaperRobot: Incremental Draft Generation of Scientific Ideas
PerceptualSimilarity
LPIPS metric. pip install lpips
PyTorch-StudioGAN
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
repgan
Official code of REPGAN (Reparameterized Sampling for Generative Adversarial Networks)
RepVGG
RepVGG: Making VGG-style ConvNets Great Again
sefa
[CVPR 2021] Closed-Form Factorization of Latent Semantics in GANs
Self-Attention-GAN
Pytorch implementation of Self-Attention Generative Adversarial Networks (SAGAN)
Series2Image
Encoding time series as images using GAF operation by pyts.
TimeGAN
Codebase for Time-series Generative Adversarial Networks (TimeGAN) - NeurIPS 2019
timegan-pytorch-1
This repository holds the code for the reimplementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch
venus
Filecoin Full Node Implementation in Go