Google Summer of Code blog posts

Introduction

This is a collection of blog posts from GSoC students who worked with ML4SCI.

Google Summer of Code 2024

"Quantum transformer for High Energy Physics Analysis at the LHC" by Alessandro Tesi
"Self-Supervised Learning for End-to-End Particle Reconstruction for the CMS Experiment" by Riccardo Tripodi
"Equivariant Vision Networks for Predicting Planetary Systems’ Architectures" by Murariu Alexandra
"Equivariant quantum neural networks for High Energy Physics Analysis at the LHC" by Lázaro Raúl Díaz Lievano
"Physics-Guided Machine Learning" by Ashutosh Ojha
"Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC" by Haemanth Velmurugan
"QMLHEP - Lie-Equivariant Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC" by Jogi Suda Neto
"Masked Autoencoders for Efficient End-to-End Particle Reconstruction and Compression for the CMS Experiment" by Shashank Shekhar Shukla
"Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System" by Vishak K Bhat
"Super-Resolution of Gravitational Lensing using Denoising Auto Encoders" by Atal Gupta
"Learning quantum representations of classical high-energy physics data with contrastive learning" by Sanya Nanda
"Learning Representation Through Self-Supervised Learning on Real Gravitational Lensing Images" by Sreehari Dinesh Iyer
"EVOLUTIONARY AND TRANSFORMER MODELS FOR SYMBOLIC REGRESSION" by Samyak Jha
"Exoplanet Atmosphere Characterization" by Gaurav Shukla
"Contrastive Representation Learning for High Energy Physics" by DO LE DUY
"Learning quantum representations of classical high energy physics data with contrastive learning" by Amey Bhatuse
"Implementation of Quantum Generative Adversarial Networks to Perform HEP Analysis at LHC" by Adithya Penagonda
"Genie : Non-local GNNs for Jet Classification" by Tanmay Bakshi
"Diffusion models for Gravitational Lensing Simulations" by J Rishi
"Masked Auto-Encoders for Efficient End-to-End Particle Reconstruction and Compression for the CMS Experiment" by Lokesh Badisa
"Transformer Models for Symbolic Calculations of Squared Amplitudes in HEP" by Ritesh Bhalerao
"Evolutionary and Transformer Models for Symbolic Regression" by Aryamaan Thakur
"Quantum Diffusion Model for HEP" by Masha Baidachna
"Physics-Informed Unsupervised Super-Resolution of Lensing Images" by Anirudh Shankar

Google Summer of Code 2023

"Symbolic empirical representation of squared amplitudes in high-energy physics" by Neeraj Anand
"Self-Supervised Learning for Strong Gravitational Lensing" by Yashwardhan Deshmukh
"Equivariant Neural Network for Signatures of Dark Matter Morphology in Strong Lensing Data" by Geo Jolly
"Quantum Transformers" by Marçal Comajoan Cara
"Quantum Generative Adversarial Networks for HEP event generation the LHC" by Tom Magorsch
"Reconstruction and Classification of Particle Collisions with Masked Transformer Autoencoders" by Eric Reinhardt
"Updating the DeepLense Pipeline" by Saranga Mahanta
"Equivariant Quantum Neural Networks" by Zhongtian Dong
"Deriving planetary surface composition from orbiting observations from spacecraft" by Sandeepan Dhoundiyal
"Diffusion Models for Fast Detector Simulation" by Akshit Choudhari
"Invariant and Equivariant Classical and Quantum Graph Neural Networks" by Roy T. Forestano

Google Summer of Code 2022

"Quantum Autoencoders for HEP Analysis at the LHC" by Tom Magorsch
"Updating the DeepLense Pipeline" by Saranga Mahanta
"Quantum Generative Adversarial Networks for High Energy Physics Analysis at the LHC" by Amey Bhatuse
"Transformers for Dark Matter Morphology with Strong Gravitational Lensing" by Archil Srivastava
"Graph Neural Networks for End-to-End Particle Identification with the CMS Experiment" by Xin Yi
"Fast Accurate Empirical Representation of Histograms" by Aaron Mayer
"Domain Adaptation for Gravitational Lens finding" by Mriganka Nath
"Deep Regression Exploration" by Zhongchao Guan
"Benchmarking Vision Transformers for Classification of Dark Matter Substructure" by Kartik Sachdev
"Deep Regression for Exploring Dark Matter" by Yurii Halychanskyi

Google Summer of Code 2021

"End-to-End Deep Learning Reconstruction for CMS Experiment" by Purva Chaudhari
"GSoC 2021 with ML4SCI \| The NMR Project" by Anantha S. Rao
"Fantastic Google Summer of Code Experiences and How I Found them" by Anis Ismail
"Dimensionality Reduction for Galaxy Evolution" by Jakub Rybak
"GSoC 2021 with ML4Sci: Domain Adaptation for Decoding Dark Matter" by Marcos Tidball
"GSOC 2021 with ML4SCI \| Deep Regression for Exploring Dark Matter" by Yurii Halychanskyi
"GSoC 2021 with ML4Sci \| Equivariant Neural Networks for Classification of Dark Matter Substructure" by Apoorva Vikram Singh
"GSoC 2021 — Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System" by Emre Kurtoglu
"Machine Learning Model for the Planetary Albedo" by Sofia Strukova
"Building a Machine Learning Model for the Albedo of Mercury" by Giorgos Pipilis
"GSoC 2021 — Personal Experience (Working with ML4SCI)" by Ehsan
"GSoC 2021 with ML4Sci \| Background Estimation with Neural Autoregressive Flows" by Sinan Gencoglu
"Google Summer of Code 2021" by Amey Varhade

Contacts

ML4SCI GSoC Admins ml4-sci@cern.ch