Machine Learning for Science (ML4SCI)

Machine learning applications in science

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Projects

Contributor

Sofia Strukova

Machine Learning Model for the Planetary Albedo

The goal of the project is to use ML techniques to identify relationships between planetary mapped datasets, with the goal of providing deeper...

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Contributor

Apoorva Vikram Singh

Equivariant Neural Networks for Dark Matter Morphology with Strong Gravitational Lensing

The study of substructures in the dark matter has shown signs of promise to deliver on the open-ended and long-standing problem of the identity of...

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Contributor

Emre Kurtoglu

Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System

The Compact Muon Solenoid (CMS) is a detector at the Large Hadron Collider (LHC) located near Geneva, Switzerland. The CMS experiment detects the...

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Contributor

Ali A. Hariri

On the potential of graph-based models in High Energy Physics

The Large Hadron Collider (LHC) at CERN is the world's highest energy particle accelerator, delivering the highest energy proton-proton collisions...

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Contributor

Georgios Pipilis

Machine Learning Model for the Albedo of Mercury

Using Deep Learning techniques in order to model the relationship between the planetary albedo and chemical composition of Mercury.

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Contributor

Yurii Halychanskyi

Direct Objective Function for Anomaly Detection

Currently, DeepLense supports the following models for unsupervised dark matter classification: - Adversarial Autoencoder - Convolutional...

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Contributor

Muhammad Ehsan ul Haq

Background Estimation with Neural AutoRegressive Flows

Neural AutoRegressive Flows are one of the most recent addition to the family of autoregressive flows. By using NAFs, probability density estimation...

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Contributor

Purva Chaudhari

End-to-End Deep Learning Reconstruction for CMS Experiment

One of the important aspects of searches for new physics at the Large Hadron Collider (LHC) involves the identification and reconstruction of single...

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Contributor

Shravan Chaudhari

Graph Neural Networks for End-to-End Particle Identification with the CMS Experiment

This project focuses on the study and implementation of Graph Neural Networks (GNNs) for low-momentum Tau Particle Identification using the CMS Open...

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Contributor

Aditya Ahuja

Normalizing Flows for Fast Detector Simulation

DeepFalcon is an ultra-fast non-parametric detector simulation package. This project aims to extend DeepFalcon by adding functionality for Graph...

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Contributor

Chi Lung Cheng

Quple - Quantum GAN

The proposed project "Quple - Quantum GAN" serves as an extension to the 2020 GSoC project "Quple" with a major focus on the implementation of...

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Contributor

Jakub Rybak

Dimensionality Reduction for Studying Diffuse Circumgalactic Medium

This project will seek to identify dimensionality-reduction methods that achieve a reduction in the number of features while maintaining predictive...

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Contributor

Eraraya Ricardo Muten

Quantum Convolutional Neural Networks for High-Energy Physics Analysis at the LHC

One of the challenges in High-Energy Physics (HEP) is events classification, which is to predict whether an image of particle jets belongs to events...

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Contributor

Sinan Gençoğlu

Background Estimation with Neural Autoregressive Flows Proposal

Data-driven background estimation is crucial for many scientific searches, including searches for new phenomena in experimental datasets. Neural...

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Contributor

Amey Varhade

Machine Learning for Turbulent Fluid Dynamics

Our understanding of Turbulence is still not very clear, studying fluid transitions to turbulence still poses challenging problems. The Navier-Stokes...

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Contributor

Anis Ismail

End-to-End Deep Learning Regression for Measurements with the CMS Experiment

Experiments conducted at the Large Hadron Collider (LHC) are the source of the most important discoveries in new physics. One of the most prominent...

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Contributor

Anantha Rao

Decoding quantum states through Nuclear Magnetic Resonance

At low temperatures, many materials transition into an electronic phase which cannot be classified as a simple metal or insulator, and quantum phases...

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Contributor

Marcos Tidball

Domain Adaptation for Decoding Dark Matter with Strong Gravitational Lensing

Dark matter is one of the biggest questions in current cosmology, and many different theories were created to try to explain it. One of the...

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Contributor

Sophia He

Uncovering the Enigma of Type-Ia Supernovae: Thermonuclear Supernova Classification via their Nuclear Signatures

Fundamental questions about Thermonuclear Supernovae (Type-Ia or SNeIa), the beacons visible across the universe, remain unanswered. Using the...

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