BillyTheKids-QRR's starred repositories
KAIST-AI-NeurIPS2019-MicroNet-2nd-place-solution
NeurIPSCD2019, MicroNet Challenge hosted by Google, Deepmind Researcher, "Efficient Model for Image Classification With Regularization Tricks".
pytorch-loss
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
class-balanced-loss
Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019
Class-balanced-loss-pytorch
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
big_O_analysis
Contains examples to practice determining big O time and space complexity.
pytorch-OpCounter
Count the MACs / FLOPs of your PyTorch model.
symbolic-dynamics
A symbolic dynamics package for Python
DL-based-Intelligent-Diagnosis-Benchmark
Source codes for the paper "Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study"
Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
PHMGNNBenchmark
this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
SinkhornAutoDiff
Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm
pytorch-fid
Compute FID scores with PyTorch.
sap-voicebox
Speech Processing Toolbox for MATLAB
Voice-Separation-and-Enhancement
A framework for quick testing and comparing multi-channel speech enhancement and separation methods, such as DSB, MVDR, LCMV, GEVD beamforming and ICA, FastICA, IVA, AuxIVA, OverIVA, ILRMA, FastMNMF.
Aggregates-Database-based-on-ACGAN
improved by ACWGAN-gp
PyTorch-1D-ACGAN-Data-Augmentation
PyTorch-1D-ACGAN for data generation. It can also work as classfier
PyTorch-GAN-Shop
Official PyTorch implementation of the paper: Contrastive Generative Adversarial Networks
PyTorch-StudioGAN
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
GANs-for-1D-Signal
implementation of several GANs with pytorch
GANFORCWRU
New GAN models in dataset of CWRU
Motor-Fault-Diagnosis
for my thesis work
CatGAN-bearing-faults
Implementation of categorical generative adversarial networks for unsupervised bearing fault diagnostics
VAE-CWGAN-GP
Chiller Fault Diagnosis based on VAE Enabled Generative Adversarial Networks