GitHub

Learning Regularization for Graph Inverse Problems (GRIPs)

This repository contains the source code for our AAAI-2025 paper. Comments have been incorporated into the python scripts to help with clarity. In recent years, Graph Neural Networks (GNNs) have been ...
IEEE

Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse Problems

Abstract: The majority of model-based learned image reconstruction methods in medical imaging have been limited to uniform domains, such as pixelated images. If the underlying model is solved on ...
GitHub

Struct2GO:protein function prediction based on Graph pooling algorithm and AlphaFold2 ...

Struct2GO is a protein function prediction model based on self-attention graph pooling, which utilizes structural information from AlphaFold2 to augment the accuracy and generality of the model's ...
IEEE

Deep Inverse Reinforcement Learning for Objective Function Identification in Bidding Models

Abstract: Due to the deregulation of power systems worldwide, bidding behavior simulation research has gained prominence. One crucial element in these studies is accurately defining and modelling the ...
Investopedia

Understanding Production Efficiency: Definitions and Measurements

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Vikki Velasquez is a researcher and writer ...