基于LSPosed框架的运动模拟器使用教程

Siamese-based ConviMixer combined with few-shot learning for classification under limited data

A few shot learning repository for bearing fault diagnosis.

Benchmark code for optimizers of bearing fault diagnosis. This code provides moduled features of data download, preprocessing, training, and logging.

University of Ottawa Rolling-element Dataset – Vibration and Acoustic Faults under Constant Load and Speed conditions (UORED-VAFCLS)

Bearing fault diagnosis based on biphasic current

A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification

Classify ECG signals into predefined categories based on heartbeat abnormality by transforming time series to images

Incomplete time series classification using GAN and RNNs

A PyTorch Time Series Classification ResNet Model

PyTorch implementation of "Multi-scale Convolutional Neural Network for Time Series Classification - Cui et al. (2016)"

Time Series Generative Adversarial Network implementation in PyTorch

Time Series Classification Benchmark with LSTM, VGG, ResNet

Using Grid Search and Bayesian Hyperparameter search to train CNN and FFNN on MNIST

Pytorch wrapper for grid search of hyperparameters

Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search https://arxiv.org/abs/1807.06906

parallel hyperparameter search

Hyperparameter Tuning in LSTM using Genetic Algorithm, Bayesian Optimization, Random Search, Grid Search.

GTFE-Net: A Gramian Time Frequency Enhancement CNN for bearing fault diagnosis

i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension…

Comparison of Bayesian hyperparameter optimization with grid search and random search, on neural networks, decision trees, random forests, and KNN

Hyperpatameter Bayesian Optimization for Image Classification in PyTorch

We implement a convolutional neural network for the Fashion MNIST dataset and use bayesian optimization to tune hyperparameters

Genetic Algorithm which optimizes Convolutional Neural Networks' architecture for image classification tasks.

Repository containing the implementation used in the experiments presented in "Optimizing a Convolutional Neural Network using Particle Swarm Optimization"