René's URL Explorer Experiment


Title: Blogs

Mail addresses
ml4-sci@cern.ch

direct link

Domain: ml4sci.github.io

NoneIE=edge

Links:

Machine Learning for Sciencehttps://ml4sci.github.io/
Activitieshttps://ml4sci.github.io/index.html
Google Summer of Code 2021https://ml4sci.github.io/activities/gsoc2021.html
Google Summer of Code 2022https://ml4sci.github.io/activities/gsoc2022.html
Google Summer of Code 2023https://ml4sci.github.io/activities/gsoc2023.html
Google Summer of Code 2024https://ml4sci.github.io/activities/gsoc2024.html
Google Summer of Code 2025https://ml4sci.github.io/activities/gsoc2025.html
Google Summer of Code 2026https://ml4sci.github.io/activities/gsoc2026.html
Hackathon 2020https://ml4sci.github.io/activities/hackathon2020.html
Hackathon 2021https://ml4sci.github.io/activities/hackathon2021.html
Contributor Publicationshttps://ml4sci.github.io/activities/papers.html
Blogshttps://ml4sci.github.io/activities/studentblogs.html
"Physics Informed Neural Network for Diffusion Equation (PINNDE)" by Sijil Josehttps://medium.com/@sijiljose.999/gsoc-2025-with-ml4sci-part-i-physics-informed-neural-network-for-diffusion-equation-pinnde-491d46a5b84d
"Learning Symbolic Expressions from Data Clouds" by Krish Malikhttps://medium.com/@krishmalikus/learning-symbolic-expressions-from-data-clouds-d186f05435bd
"Exploring Squared Amplitudes in High Energy Physics" by Ayush Mishrahttps://medium.com/@ayush89718/exploring-squared-amplitudes-in-high-energy-physics-with-ml4sci-my-gsoc-journey-part-2-2c1ff217f10e
"State Space Models for Squared Amplitude Calculations" by Karaka Prasanth Naiduhttps://medium.com/@prasanthnaidu31k/state-space-models-for-squared-amplitude-calculations-618b9ea4a4fd
"Exploring Machine Learning for HCAL Data Quality Monitoring" by Daksh Morhttps://medium.com/@daksh3982/exploring-machine-learning-for-hcal-data-quality-monitoring-06fee3c59bd0
"Foundational Model for Symbolic Regression in High Energy Physics" by Miche Maralhttps://medium.com/@michemarall/google-school-of-code-foundational-model-in-high-energy-physics-symbolic-regression-3d0311b01dad
"Foundation Models for Exoplanet Characterization" by Tanmay Singhalhttps://medium.com/@singhaltanmay55/foundation-models-for-exoplanet-characterization-9ab7ef402f08
"Disentangling symmetries" by Alexandra Murariuhttps://medium.com/@murariu.alexandra2002/disentangling-symmetries-gsoc25-ml4sci-e2e-41b17276d184
"Hidden Symmetry and Generators" by Avishikta Bhattacharjeehttps://medium.com/@avishiktaa.bhattacharrjee/hidden-symmetry-and-generators-2dcdb18fbee4
"The Geometry Beneath: Revealing Hidden Symmetries" by Green Kediahttps://medium.com/@greenkedia10/the-geometry-beneath-revealing-hidden-symmetries-8cadf0c8118b
"Graph Representation Learning for Fast Detector Simulation" by Rushil Singhahttps://medium.com/@rushilsingha18/gsoc-25-graph-representation-learning-for-fast-detector-simulation-at-ml4sci-97d49b85adf4
"DeepLense_Data_Processing_Pipeline_for_the_LSST" by Kartik Mandarhttps://gsoc2025.blogspot.com/
"Exploring Machine Learning for HCAL Data Quality Monitoring" by Daksh Morhttps://medium.com/@daksh3982/exploring-machine-learning-for-hcal-data-quality-monitoring-06fee3c59bd0
"Q-MAML for Variational Quantum Algorithms for High Energy Physics analysis at LHC" by Arnav Singhalhttps://medium.com/@arnavsinghal06/gsoc-25-q-maml-for-variational-quantum-algorithms-for-high-energy-physics-analysis-at-lhc-7b85a54a8924
"Diffusion model for superresolution imaging" by Aleksandr Duplinskiihttps://medium.com/@al.duplinskiy/diffusion-model-for-superresolution-imaging-c0d6ec8b8597
"Simulating Gravitational Lensing with Flow Matching" by Hamees Sayedhttps://medium.com/@hameessayed71/simulating-gravitational-lensing-with-flow-matching-gsoc-midterm-update-7d4692375ae8
"Quantum Kolmogorov-Arnold Networks for High Energy Physics Analysis at the LHC" by Ria Khatoniarhttps://medium.com/@riakhatoniar1234/gsoc-2025-quantum-kolmogorov-arnold-networks-for-high-energy-physics-analysis-at-the-lhc-a98207bf6d4c
"Foundation models for End-to-End event reconstruction for the CMS Experiment" by Aaditya Porwalhttps://medium.com/@aadityaporwal234/foundation-models-for-end-to-end-event-reconstruction-for-the-cms-experiment-08f2e1a45487
"Event Classification with Masked Transformer Autoencoders" by Thanh Nguyenhttps://medium.com/@thanhnguyen14401/gsoc-2025-with-ml4sci-event-classification-with-masked-transformer-autoencoders-6da369d42140
"Quantum Generative Adversarial Networks to Perform HEP Analysis" by Maya Mahttps://medium.com/@maya030928/exploring-quantum-generative-adversarial-network-with-gsoc-d4fdf3b3dedd
"Next-Generation Transformer Models for Symbolic Calculations of Squared Amplitudes in HEP" by Ritesh Bhaleraohttps://github.com/Riteshbhalerao11/GSoC_25
"Quantum Particle transformer for High Energy Physics Analysis at the LHC" by Alessandro Tesihttps://medium.com/@tesi.alessandro88/gsoc-25-quantum-particle-transformer-for-high-energy-physics-analysis-at-ml4sci-dad868fd53f2
"Neural Harmony – Decoding Social Interactions with CEBRA-based framework for analysing EEG data" by Maria Glushaninahttps://medium.com/@mariya.glushanina/extending-cebra-to-dyadic-neural-dynamics-my-google-summer-of-code-journey-5459134af50c
"Latent Neural Signatures in Clinical vs. Neurotypical Dyads: A CEBRA Pipeline" by Jeffrey Huanghttps://medium.com/@jeffreyhuang1009/cebra-based-data-processing-pipeline-for-mapping-time-locked-eeg-paired-sets-in-interacting-0dbec173a20f
"DeepLense: Gravitational Lens Finding" by Dhruv Srivastavahttps://github.com/EnderNinja7/HEALSwin-PINN/tree/main
"A Diffusion-Based Deep Learning Framework for Denoising Protoplanetary Disk Observations" by Chukwunwogor Faithfulhttps://medium.com/@chukwuivnez/a-diffusion-based-deep-learning-framework-for-denoising-protoplanetary-disk-observations-gsoc-4870df837409
"Quantum transformer for High Energy Physics Analysis at the LHC" by Alessandro Tesihttps://medium.com/@tesi.alessandro88/gsoc-24-quantum-transformer-for-high-energy-physics-analysis-at-ml4sci-ab8a86acdab0
"Self-Supervised Learning for End-to-End Particle Reconstruction for the CMS Experiment" by Riccardo Tripodihttps://medium.com/@riccardotripodi/self-supervised-learning-for-end-to-end-particle-reconstruction-for-the-cms-experiment-2-2-9997aa51ca7d
"Equivariant Vision Networks for Predicting Planetary Systems’ Architectures" by Alexandra Murariuhttps://medium.com/@murariu.alexandra2002/gsoc-ml4sci-exxa-equivariant-vision-networks-for-predicting-planetary-systems-architectures-b6f7c5846bda
"Equivariant quantum neural networks for High Energy Physics Analysis at the LHC" by Lázaro Raúl Díaz Lievanohttps://medium.com/@214lievano/equivariant-quantum-neural-networks-for-high-energy-physics-analysis-at-the-lhc-59b55ed3d43e
"Physics-Guided Machine Learning" by Ashutosh Ojhahttps://medium.com/@ojhaaashutosh1005/gsoc24-with-ml4sci-physics-guided-machine-learning-final-evaluation-0814ed47bbd2
"Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC" by Haemanth Velmuruganhttps://medium.com/@haemanth10/quantum-graph-neural-networks-9cde9613a8d5
"QMLHEP - Lie-Equivariant Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC" by Jogi Suda Netohttps://jogisuda.github.io/posts/2024/07/lie-eqgnn/
"Masked Autoencoders for Efficient End-to-End Particle Reconstruction and Compression for the CMS Experiment" by Shashank Shekhar Shuklahttps://medium.com/@shuklashashankshekhar863/masked-autoencoders-for-efficient-end-to-end-particle-reconstruction-and-compression-for-the-cms-fdd7b941a2bb
"Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System" by Vishak K Bhathttps://medium.com/@vishak.bhat5/gsoc24-with-ml4sci-graph-neural-networks-for-particle-momentum-estimation-in-the-cms-trigger-e67e3f43a292
"Super-Resolution of Gravitational Lensing using Denoising Auto Encoders" by Atal Guptahttps://medium.com/@guptaatal/single-image-super-resolution-using-denoising-auto-encoder-f05facda6485
"Learning quantum representations of classical high-energy physics data with contrastive learning" by Sanya Nandahttps://sanyananda.github.io/ML4Sci_QuantumContrastiveLearning/
"Learning Representation Through Self-Supervised Learning on Real Gravitational Lensing Images" by Sreehari Dinesh Iyerhttps://iyersreehari.github.io/gsoc24-blog-deeplense-ssl/
"EVOLUTIONARY AND TRANSFORMER MODELS FOR SYMBOLIC REGRESSION" by Samyak Jhahttps://medium.com/@samyakjha71/symbolic-regression-gsoc-24-final-evaluations-40aea5aad6dd
"Exoplanet Atmosphere Characterization" by Gaurav Shuklahttps://medium.com/@shuklag554/exoplanet-atmosphere-characterization-gsoc24-ml4sci-part-2-96392e3ba190
"Contrastive Representation Learning for High Energy Physics" by DO LE DUYhttps://duydl.github.io/blogs/end-term-report-gsoc24.html
"Learning quantum representations of classical high energy physics data with contrastive learning" by Amey Bhatusehttps://medium.com/@ameybhatuse315/quantum-graph-contrastive-learning-for-high-energy-physics-aa6e49eaa34f
"Implementation of Quantum Generative Adversarial Networks to Perform HEP Analysis at LHC" by Adithya Penagondahttps://medium.com/@swheatdreamz/whos-at-loss-0b921b3e1bb4
"Genie : Non-local GNNs for Jet Classification" by Tanmay Bakshihttps://medium.com/@pankajbakshi88/non-local-gnns-for-jet-classification-going-beyond-graphs-5b62286e5c58
"Diffusion models for Gravitational Lensing Simulations" by J Rishihttps://medium.com/@rishirswamy/gsoc-24-with-ml4sci-part-2-diffusion-models-for-gravitational-lensing-simulations-7c667be4bf45
"Masked Auto-Encoders for Efficient End-to-End Particle Reconstruction and Compression for the CMS Experiment" by Lokesh Badisahttps://medium.com/@lokeshbadisa657/gsoc-2024-with-ml4sci-masked-auto-encoders-for-efficient-end-to-end-particle-reconstruction-and-60ea4dde539e
"Transformer Models for Symbolic Calculations of Squared Amplitudes in HEP" by Ritesh Bhaleraohttps://www.linkedin.com/posts/ritesh-bhalerao_gsoc-activity-7256869917877026816-2TCY?utm_source=share&utm_medium=member_desktop
"Evolutionary and Transformer Models for Symbolic Regression" by Aryamaan Thakurhttps://medium.com/@aryamaanthakur/transformers-meet-evolution-a-hybrid-approach-to-symbolic-regression-final-progress-gsoc-0de041ac013d
"Quantum Diffusion Model for HEP" by Masha Baidachnahttps://medium.com/@mashapotatoes/gsoc-quantum-diffusion-model-for-high-energy-physics-part-ii-6e693d625931
"Physics-Informed Unsupervised Super-Resolution of Lensing Images" by Anirudh Shankarhttps://medium.com/@anirudhshankar99/physics-informed-unsupervised-super-resolution-of-lensing-images-gsoc-2024-x-ml4sci-51cedc1cfb00
"Quantum Machine Learning For Exoplanet Characterization" by Sourish Phatehttps://medium.com/@sourishphate/quantum-machine-learning-for-exoplanet-characterization-gsoc-25-ml4sci-c6c6cb4590b9
"Symbolic empirical representation of squared amplitudes in high-energy physics" by Neeraj Anandhttps://medium.com/@neerajanandfirst/my-journey-to-google-summer-of-code-2023-with-ml4sci-8822ce64464a
"Self-Supervised Learning for Strong Gravitational Lensing" by Yashwardhan Deshmukhhttps://medium.com/@yaashwardhan/self-supervised-learning-for-strong-gravitational-lensing-part1-5a049e976b51
"Equivariant Neural Network for Signatures of Dark Matter Morphology in Strong Lensing Data" by Geo Jollyhttps://kingjuno.github.io/gsoc/
"Quantum Transformers" by Marçal Comajoan Carahttps://salcc.github.io/blog/gsoc23
"Quantum Generative Adversarial Networks for HEP event generation the LHC" by Tom Magorschhttps://www.tommago.com/posts/gsoc23/
"Reconstruction and Classification of Particle Collisions with Masked Transformer Autoencoders" by Eric Reinhardthttps://medium.com/@eric0reinhardt/gsoc-2023-with-ml4sci-reconstruction-and-classification-of-particle-collisions-with-masked-bab8b38958df
"Updating the DeepLense Pipeline" by Saranga Mahantahttps://medium.com/@saranga.boo/updating-the-deeplense-pipeline-part-2-gsoc-2023-with-ml4sci-299a48d0dd23
"Equivariant Quantum Neural Networks" by Zhongtian Donghttps://medium.com/@zhontiandong/equivariant-quantum-neural-networks-be4ba231c457
"Deriving planetary surface composition from orbiting observations from spacecraft" by Sandeepan Dhoundiyalhttps://medium.com/@dsandeepan995/gsoc23-with-ml4sci-deriving-planetary-surface-composition-from-orbiting-observations-from-46f81885c9be
"Diffusion Models for Fast Detector Simulation" by Akshit Choudharihttps://medium.com/@akshit.chodhary/wrap-up-gsoc-2023-ml4sci-2f98adaa21ae
"Invariant and Equivariant Classical and Quantum Graph Neural Networks" by Roy T. Forestanohttps://royforestano.github.io/blog/2023/2023-gsoc-ml4sci-qmlhep/
"Quantum Autoencoders for HEP Analysis at the LHC" by Tom Magorschhttps://www.tommago.com/posts/gsoc/
"Updating the DeepLense Pipeline" by Saranga Mahantahttps://medium.com/@saranga.boo/updating-the-deeplense-pipeline-gsoc-2022-with-ml4sci-deb9f20cc928
"Quantum Generative Adversarial Networks for High Energy Physics Analysis at the LHC" by Amey Bhatusehttps://medium.com/@ameybhatuse315/quantum-generative-adversarial-networks-for-high-energy-physics-analysis-at-the-lhc-google-summer-98e2ed67a55e
"Transformers for Dark Matter Morphology with Strong Gravitational Lensing" by Archil Srivastavahttps://medium.com/@archilsrivastava/transformers-for-dark-matter-morphology-with-strong-gravitational-lensing-gsoc-2022-with-ml4sci-b34a03d30114
"Graph Neural Networks for End-to-End Particle Identification with the CMS Experiment" by Xin Yihttps://medium.com/@haku20010427/gsoc2022-ml4sci-graph-neural-networks-for-end-to-end-particle-identification-with-the-cms-e38a7abf2bc5
"Fast Accurate Empirical Representation of Histograms" by Aaron Mayerhttps://medium.com/@asmayer1216/gsoc-2022-with-ml4sci-e350db0907cd
"Domain Adaptation for Gravitational Lens finding" by Mriganka Nathhttps://mrinath.medium.com/domain-adaptation-for-gravitational-lens-finding-gsoc-22-ml4sci-7b70b2be6d6b
"Deep Regression Exploration" by Zhongchao Guanhttps://medium.com/@gg884691896/gsoc-2021-with-ml4sci-deep-regression-exploration-34d5d8fb4643
"Benchmarking Vision Transformers for Classification of Dark Matter Substructure" by Kartik Sachdevhttps://medium.com/@sachdev.kartik25/benchmarking-vision-transformers-for-classification-of-dark-matter-substructure-gsoc-2022-with-6ec7711cc32d
"Deep Regression for Exploring Dark Matter" by Yurii Halychanskyihttps://medium.com/@yuriihalyc/gsoc-2022-with-ml4sci-deep-regression-for-exploring-dark-matter-3f2f1badb60f
"End-to-End Deep Learning Reconstruction for CMS Experiment" by Purva Chaudharihttps://medium.com/@purva.chaudhari02/google-summer-of-code-2021-5cf8ef45d2d2
"GSoC 2021 with ML4SCI | The NMR Project" by Anantha S. Raohttps://medium.com/@aanantha.s.rao/gsoc-2021-with-ml4sci-the-nmr-project-1a5e8995af9
"Fantastic Google Summer of Code Experiences and How I Found them" by Anis Ismailhttps://anisismail09.medium.com/fantastic-google-summer-of-code-experiences-and-how-i-found-them-dd1c5b09a364
"Dimensionality Reduction for Galaxy Evolution" by Jakub Rybakhttps://medium.com/@jbrybak/dimensionality-reduction-for-galaxy-evolution-82235391dcd3
"GSoC 2021 with ML4Sci: Domain Adaptation for Decoding Dark Matter" by Marcos Tidballhttps://medium.com/@marcostidball/gsoc-2021-with-ml4sci-domain-adaptation-for-decoding-dark-matter-bf0380898aed
"GSOC 2021 with ML4SCI | Deep Regression for Exploring Dark Matter" by Yurii Halychanskyihttps://medium.com/@yuriihalyc/gsoc-2021-with-ml4sci-deep-regression-for-exploring-dark-matter-32691c46adfa
"GSoC 2021 with ML4Sci | Equivariant Neural Networks for Classification of Dark Matter Substructure" by Apoorva Vikram Singhhttps://medium.com/@singhapoorva388/gsoc-2021-with-ml4sci-equivariant-neural-networks-for-classification-of-dark-matter-substructure-64ef3877477a
"GSoC 2021 — Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System" by Emre Kurtogluhttps://medium.com/@emre.kurt.96/gsoc-2021-graph-neural-networks-for-particle-momentum-estimation-in-the-cms-trigger-system-2216e4e4d005
"Machine Learning Model for the Planetary Albedo" by Sofia Strukovahttps://gist.github.com/strukovas/7ffcc9edd823c5bf7afa7541ae04f647
"Building a Machine Learning Model for the Albedo of Mercury" by Giorgos Pipilishttps://gist.github.com/giorgos314/212ed883cb097e3012e36f24f91fb52f
"GSoC 2021 — Personal Experience (Working with ML4SCI)" by Ehsanhttps://medium.com/@ehsanulhaq18/gsoc-2021-personal-experience-working-with-ml4sci-921c684e30ee
"GSoC 2021 with ML4Sci | Background Estimation with Neural Autoregressive Flows" by Sinan Gencogluhttps://medium.com/@sinan.gencogluu/gsoc-2021-with-ml4sci-background-estimation-with-neural-autoregressive-flows-b164e247e183
"Google Summer of Code 2021" by Amey Varhadehttps://yemaedahrav.github.io/ameygsocblog/
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