Summary of GSoC 2022 Projects and Supervisors

Full List of Proposals

Background Estimation with Neural AutoRegressive Flows
Deep Regression Techniques for Decoding Dark Matter with Strong Gravitational Lensing
Diffusion Models for Fast Detector Simulation
End-to-End Deep Learning Reconstruction for CMS Experiment
End-to-End Deep Learning Regression for Measurements with the CMS Experiment
Equivariant Neural Networks for Dark Matter Morphology with Strong Gravitational Lensing
Fast Accurate Symbolic Empirical Representation Of Histograms
Finding Exoplanets with Astronomical Observations
Graph Neural Networks for End-to-End Particle Identification with the CMS Experiment
Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System
Graph Representation Learning for Fast Detector Simulation
Graph Transformers for Fast Detector Simulation
Gravitational Lens Finding for Dark Matter Substructure Pipeline
Implementation of Quantum Generative Adversarial Networks to Perform High Energy Physics Analysis at the LHC
Implementation of Quantum Variational Autoencoders to Perform High Energy Physics Analysis at the LHC
Machine Learning Model for the Albedo of Mercury
Optimal Transport in High Energy Physics
Quantum Convolutional Neural Networks for High Energy Physics Analysis at the LHC
Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC
Revealing the Identities of Thermonuclear Scenarios Using the Ultraviolet, Optical, and Infrared (UVOIR) Light Curves of Type-Ia Supernovae
Symbolic empirical representation of squared amplitudes in high-energy physics
Thermonuclear Supernova Classification via their Multi-Wavelength Signatures
Transformers for Dark Matter Morphology with Strong Gravitational Lensing
Updating the DeepLense Pipeline
Vision Transformers for End-to-End Particle Reconstruction for the CMS Experiment