The source code for NeurIPS 2020 paper "Graph Policy Network for Transferable Active Learning on Graphs"

[ICLR2025] Kolmogorov-Arnold Transformer

Tidy multi-material machine tool wear dataset for prognostics and health monitoring.

Code for "Interpretable Prognostics with Concept Bottleneck Models"

The project focuses on prediction of RUL (Remaining Useful Life) of aircraft engine. The acitivity is carried out in PyTorch frameowrk using at first a simple feedforward neural network, followed b…

A Digital Twin prototype for aircraft engine health management in order to identify possible faults and to predict its remaining useful life

Multi-Objective Optimization of ELM for RUL Prediction

Exploratory Data Analysis of the popular dataset N-CMAPSS (source: https://data.nasa.gov/Aerospace/CMAPSS-Jet-Engine-Simulated-Data/ff5v-kuh6) and Remaining useful life prediction (RUL) through thr…

Bayesian Neural Networks to predict RUL on N-CMAPSS

Estimating Remaining Useful Life of a Turbofan Jet Engine using NCMAPSS dataset

N-CMAPSS data preparation for Machine Learning and Deep Learning models. (Python source code for new CMAPSS dataset)

Implementation on how to use Kolmogorov-Arnold Networks (KANs) for classification and regression tasks.

Research on the RUL prediction method based on diffusion model and graph neural network on N-CMAPSS dataset

RUL prediction of engines from CMAPSS Data

Implementation of GCU-Transformer for RUL Prediction on CMAPSS

Evolutionary Neural Architecture Search on Transformers for RUL Prediction

AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting. This is my implementation of this model that is to be integrated into an experimental platform that …

Official repository for the paper "Scalable Spatiotemporal Graph Neural Networks" (AAAI 2023)

The official implementation of 'Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulation'.

A physics-integrated spatiotemporal graph neural network with fundamental diagram learner for highway traffic flow prediction

This project develops a traffic prediction model combining Graph Attention Networks (GAT) and Transformer architecture to analyze spatiotemporal data from Paris traffic probes. It enhances traffic …

A Pytorch Implementation of "Attention is All You Need" and "Weighted Transformer Network for Machine Translation"

Transformer related optimization, including BERT, GPT

Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)

Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs

A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold N…