Official PyTorch Implementation for the "Active Learning with a Noisy Annotator" paper.
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Updated
Jun 9, 2025 - Python
Official PyTorch Implementation for the "Active Learning with a Noisy Annotator" paper.
Spatiotemporal Gaussian process modeling for environmental data: non-stationary PDE prior, deep kernels, multi-fidelity fusion, and A-optimal sampling.非稳态 PDE + 核深度学习 + 多保真 Co-Kriging + 主动采样的物理约束克里金方法,用于复杂时空环境建模与预测
PyTorch implementation of our paper "Rethinking Deep Active Learning for Medical Image Segmentation: A Diffusion and Angle-based Framework"
Analysis code for the `mpib_sp_eeg` experiment
SOLAR: a seven-agent bot and misinformation detection framework, audited and extended into label-efficient evaluation of detectors and LLM judges. Small random human-labeled samples give valid intervals, pilot-based scorer choice and always-valid drift monitoring. Includes browser tools.
OGAS: Generative Active Sampling for Online PDE Surrogate Training
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