| Background Estimation with Neural AutoRegressive Flows |
| Cosmic-Ray Imaging Studies via Mission-Imagery from Space (CRISMIS) |
| Decoding quantum states through nuclear magnetic resonance |
| Deep Regression Techniques for Decoding Dark Matter with Strong Gravitational Lensing |
| Dimensionality Reduction for Studying Diffuse Circumgalactic Medium |
| Domain Adaptation for Decoding Dark Matter with Strong Gravitational Lensing |
| 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 |
| Equivariant Neural Networks to explore the underlying symmetries in particle physics events |
| 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 |
| Implementation of Quantum Generative Models to Perform High Energy Physics Analysis at the LHC |
| Machine Learning Model for the Albedo of Mercury |
| Machine Learning Model for the Lunar Albedo |
| Machine Learning for Turbulent Fluid Dynamics |
| Normalizing Flows for Fast Detector Simulation |
| Quantum Convolutional Neural Networks for High Energy Physics Analysis at the LHC |
| Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC |
| Thermonuclear Supernova Classification via their Nuclear Signatures |