This project explores the application of reinforcement learning algorithms to bridge infrastructure maintenance, balancing condition improvement and budget constraints. Inspired by the InfraPlanner…

list of open wind turbine data sets

This repository reimplemented "MC Dropout" by tensorflow 2.0 Eager Extension.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

source codes for EEGWaveNet: Multi-Scale CNN-Based Spatiotemporal Feature Extraction for EEG Seizure Detection (IEEE Transactions on Industrial Informatics)

MEC : Multi-scale Deep Embedding and Clustering for Single Cell Hi-C Data

Intuitionistic fuzzy c-means algorithm based on kernels hybridized with a metaheuristic applied to data classification

Enhancing Electric Vehicle Routing Efficiency Through K-Means Clustering and Genetic Algorithm Optimization

max_sliced_wasserstein_distance

Sliced Wasserstein Distance (SWD) in PyTorch

😴 DeepSleep2 is a compact U-Net-inspired convolutional neural network with 740,551 parameters, designed to predict non-apnea sleep arousals from full-length multi-channel polysomnographic recording…

An optimization technique to optimize K-Means algorithm which is used to cluster a dataset.

Enhancing the performance of high dimensional automatic data clustering using Particle Swarm Optimization (PSO) algorithm employing Autoencoder in Stock Market data.

Pytorch Deep Clustering with Convolutional Autoencoders implementation

Implementation of Gaussian Mixture Variational Autoencoder (GMVAE) for Unsupervised Clustering

PyTorch implementations of Generative Adversarial Networks.

使用深度学习模型LSTM和ConvLSTM结合Attention，对金融衍生品的成交持仓比指标进行预测

GAN based ConvLSTM in precipitation prediction (Trial Version)

This repository contains the pytorch code for the 2023 ICASSP paper "Preformer: Predictive Transformer with Multi-Scale Segment-wise Correlations for Long-Term Time Series Forecasting”

The code of DAST

matlab code of wiener process example

Variance Gamma distribution (Python): pdf, cdf, rand and fit.

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…

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Extended Kalman Filter

This is Python implementation of EKF(Extended Kalman filter) for state of charge estimation of battery

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…