Implementation of ML4SCI evaluation tasks for GSoC 2025, featuring deep learning approaches for gravitational lensing analysis including multi-class classification, lens finding with class imbalance and generative models for synthetic lensing image creation.
GSoC 2026 DeepLense test submission: Common Test I classification and Test VI.A/VI.B super-resolution on simulated and real HSC/HST lensing data.
ML4Sci GSoC 2026 - QMLHEP Evaluation Tasks
ML4SCI Genie GSoC 2026 Tasks
ML4Sci GSoC 2026 Evaluation (FASEROH): Training Seq2Seq architectures (LSTM & Transformer) to compute symbolic Taylor series expansions.
GSoC 2026 — ML4SCI DeepLense Evaluation Test: Multi-Class Classification + Gravitational Lens Finding
Evaluation pipeline for the ML4SCI DeepLense GSoC 2026 project, focusing on dark matter morphology and Equivariant Neural Networks.
tasks for Q-MAML - Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms for High Energy Physics Analysis at the LHC
Unified Python/C++ library for jet observables, HEPSIM-ready workflows, and Monte Carlo validation.
Quantum Machine Learning portfolio for ML4SCI QMLHEP, featuring QGANs, QGNNs, QRL, EQNNs, and Vision Transformers built with TensorFlow Quantum and Cirq.
Add a description, image, and links to the ml4sci topic page so that developers can more easily learn about it.
To associate your repository with the ml4sci topic, visit your repo's landing page and select "manage topics."