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 |

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 |