⚠ Archived — the upstream repository is no longer receiving updates.
GAISHI: Ghost Introgression Detector
github.com/xin-huang/gaishiGAISHI is a Python package designed for identifying ghost introgressed segments and alleles in population genetics using multiple machine learning algorithms (e.g., logistic regression, UNet++).
Sourced from
- GitHub — github.com/xin-huang/gaishi
Related resources
Foundation model for tabular data that predicts on unseen real-world tables in a single forward pass, achieving accurate small-data classification and regression without task-specific training; widely applicable to scientific datasets with limited samples (7.4K+ stars, 2022-2026)
Deep learning library for Chemistry based on Tensorflow
Pretrained time series foundation model for zero-shot forecasting across diverse scientific and real-world domains; tokenizes continuous time series into discrete bins to train transformer language models on large-scale corpora, achieving strong zero-shot generalization and competitive performance with task-specific supervised models on climate, energy, and health benchmarks (5.3K+ stars, Apache 2.0, 2024-2026)
Programmatic data labeling and weak supervision
Machine learning software for extracting structured metadata from scholarly documents