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particle-filter-based-prognostics-algorithm

Python implementation of the paper titled - "Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab"

pde-find

pg_curve

Matlab code for computing and visualization: Confusion Matrix, Precision/Recall, ROC, Accuracy, F-Measure etc. for Classification.

phycrnet

Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

pinn_wind_bearing

Python scripts for wind turbine main bearing fatigue life estimation with physics-informed neural networks

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

pisl

A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.

pit

probabilistic_rul_prediction

probnum

Probabilistic Numerics in Python.

prog_models

The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.

projectrul

to prediction the remain useful life of bearing based on 2012 PHM data

pymle

Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)

pysindy

A package for the sparse identification of nonlinear dynamical systems from data

pytorch-actorcriticrl

PyTorch implementation of DDPG algorithm for continuous action reinforcement learning problem.

pytorch-alad

PyTorch Implementation for "Adversarially Learned Anomaly Detection" (ALAD)

pytorch-center-loss

Pytorch implementation of Center Loss

pytorch-cpo

PyTorch implementation of Constrained Policy Optimization

pytorch-ddpg

Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch

pytorch-ddpg-naf

Implementation of algorithms for continuous control (DDPG and NAF).

pytorch-grad-cam

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

pytorch-loss

label-smooth, amsoftmax, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

pytorch-maddpg

A pytorch implementation of MADDPG (multi-agent deep deterministic policy gradient)

pytorch-soft-actor-critic

PyTorch implementation of soft actor critic

pytorch-transformer

pytorch implementation of Attention is all you need

pytorch-transformer-for-rul-prediction

Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.

pytorch_geometric

Geometric Deep Learning Extension Library for PyTorch

pytorch_sac

PyTorch implementation of Soft Actor-Critic (SAC)

resnet-50-cbam-pytorch

Implementation of Resnet-50 with and without CBAM in PyTorch v1.8. Implementation tested on Intel Image Classification dataset from https://www.kaggle.com/puneet6060/intel-image-classification.

rknn