Machine Learning Research to Advance Simulation Science
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Updated
Jul 23, 2022 - JavaScript
Machine Learning Research to Advance Simulation Science
PyTorch code for an effective way of making a Molecular Graph Dataset in Torch Geometric involving a pair of graphs from chemical SMILE strings
Assignments done under course COL761-Data Mining
Toxic video game classification with graph neural networks
Collection of GNN architectures for 3D shapes and graphs using NN Template
A project implementing better evaluation scenarios for community models for malicious content detection, and meta-learning GNNs to achieve better downstream adaptation.
This is the code repo for Violin, an IJCAI 2023 paper.
Temporal Graph Neural Networks for Epidemiological Forecasting - project for COSC 525: Deep Learning.
A customized version of the Relational Aware Graph Attention Network for large scale EHR records.
The goal of this project is to provide a theoretic analysis, explaining the effect of homophily on Graph Neural Network Performace, that leverages on recent results in random family networks and their geodesics, by exploring the structural effects of homophily.
Masters Thesis - Reproducible Knowledge Distillation on Graphs.
Protein Secondary Structure Prediction through Hybrid Integration of Transformers and Graph Neural Networks
cloud-based, large-scale ST-GCN with OpenStreetMap features
Accompanying code for the AISTATS 2024 paper BLIS-Net: Classifying and Analyzing Signals on Graphs
Repository for bilateral message passing GNNs
This classifier achieved the following results, "Percent humans misclassified as dogs is 1%. and "Percent of dogs correctly classified is 100%" It is very reliable when it comes to classification of dog breeds.
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