Python framework for interpretable protein prediction
Sunwoda Electronic Co., Ltd, and Tsinghua Berkeley Shenzhen Institute (TBSI) generate the TBSI Sunwoda Battery Dataset. We open-source this dataset to inspire more data-driven novel material verification, battery management research and applications.
The official implementation of our paper "TELLER: A Trustworthy Framework for Explainable, Generalizable and Controllable Fake News Detection".
[TPAMI 2025] Mixture of Gaussian-distributed Prototypes with Generative Modelling for Interpretable and Trustworthy Image Recognition
Learning semantic association rules from internet of things data
PeliCAM is a desktop application for visualizing model interpretability.
Official source codes for implementing "Design of reliable technology valuation model with calibrated machine learning of patent indicators"
Sustainability of Machine Learning Models
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