ml4sci

ML4SCI Genie GSoC 2026 Tasks

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

Unified Python/C++ library for jet observables, HEPSIM-ready workflows, and Monte Carlo validation.

Adding Submission of all the challenges

GSoC 2026 ML4SCI/QMLHEP evaluation task — an LLM agent that autonomously designs, simulates, and optimizes variational quantum circuits (VQC vs Q-KAN, PennyLane)

ML4Sci GSoC 2026 Evaluation (FASEROH): Training Seq2Seq architectures (LSTM & Transformer) to compute symbolic Taylor series expansions.

Single Image Super Resolution Using WaveMix

GSoC 2026 — ML4SCI DeepLense Evaluation Test: Multi-Class Classification + Gravitational Lens Finding

tasks for Q-MAML - Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms for High Energy Physics Analysis at the LHC

Jet classification using Autoencoder, GNN and Contrastive Learning for ML4SCI GSoC 2026

Building and Comparing Segmentation Strategies for Coronary Artery Calcium (CAC)

GSoC 2026 ML4Sci PREDICT2 evaluation submission — radiomics feature extraction for coronary calcium phenotyping

Evaluation pipeline for the ML4SCI DeepLense GSoC 2026 project, focusing on dark matter morphology and Equivariant Neural Networks.

Quantum Machine Learning portfolio for ML4SCI QMLHEP, featuring QGANs, QGNNs, QRL, EQNNs, and Vision Transformers built with TensorFlow Quantum and Cirq.