Patching Weak Convolutional Neural Network Models through Modularization and Composition. (ASE'22)
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Updated
Sep 7, 2022 - Python
Patching Weak Convolutional Neural Network Models through Modularization and Composition. (ASE'22)
Reusing Deep Neural Network Models through Model Re-engineering (ICSE'23)
Code, data, and logs for paper (IJCAI 2023) 'Improving Heterogeneous Model Reuse by Density Estimation'
Modularizing while Training: A New Paradigm for Modularizing DNN Models (ICSE'24)
LaF focuses on the comparion testing of multiple deep learning models without manual labeling.
[NeurIPS2022] Deep Model Reassembly
ZhiJian: A Unifying and Rapidly Deployable Toolbox for Pre-trained Model Reuse
Reusing Convolutional Neural Network Models through Modularization and Composition (TOSEM'23)
A curated list of Composable AI methods: Building AI system by composing modules.
Knowledge Amalgamation Engine
The official code for "Model Spider: Learning to Rank Pre-Trained Models Efficiently" (NeurIPS 2023 Spotlight)
The code repository for "Model Spider: Learning to Rank Pre-Trained Models Efficiently"
STARS Project: Example `simpy` model documentation using JupyterBook, GitHub Pages, and STRESS
STARS Project: deploying a python DES model using streamlit
A treatment simulation model implemented in CiW
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