@sachdevkartik
Hi Kartik,
I applied for GSoC 2026 with the DeepLense project and have been working on the Genie tasks.
I implemented the autoencoder and a GNN pipeline by converting jet images into graph representations using non zero pixels and k nearest neighbor edges.
I also ran a comparison across CNN, ResNet, and GNN models with evaluation metrics to understand performance differences.
Here is my updated work:
https://github.com/Sasisundar2211/ml4sci-gsoc
I am now focusing on improving the graph representation and model performance. From your experience, which direction would add the most value at this stage?
Thanks,
Sasi
@sachdevkartik
Hi Kartik,
I applied for GSoC 2026 with the DeepLense project and have been working on the Genie tasks.
I implemented the autoencoder and a GNN pipeline by converting jet images into graph representations using non zero pixels and k nearest neighbor edges.
I also ran a comparison across CNN, ResNet, and GNN models with evaluation metrics to understand performance differences.
Here is my updated work:
https://github.com/Sasisundar2211/ml4sci-gsoc
I am now focusing on improving the graph representation and model performance. From your experience, which direction would add the most value at this stage?
Thanks,
Sasi