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| title: 'NCTV: Neural Clamping Toolkit and Visualization' | |
| emoji: 🦀 | |
| colorFrom: yellow | |
| colorTo: gray | |
| sdk: static | |
| pinned: false | |
| short_description: Model-agnostic Toolkit for Neural Network Calibration | |
| This is a demo of the approach described in the following papers: | |
| - [Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration | |
| ](https://arxiv.org/abs/2209.11604) | |
| - [NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration](https://arxiv.org/abs/2211.16274) | |
| ``` | |
| @article{tang2024neural, | |
| title={{Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration}}, | |
| author={Yung-Chen Tang and Pin-Yu Chen and Tsung-Yi Ho}, | |
| journal={Transactions on Machine Learning Research}, | |
| issn={2835-8856}, | |
| year={2024}, | |
| url={https://openreview.net/forum?id=qSFToMqLcq}, | |
| } | |
| @inproceedings{hsiung2023nctv, | |
| title={{NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration}}, | |
| author={Lei Hsiung and Yung-Chen Tang and Pin-Yu Chen and Tsung-Yi Ho}, | |
| booktitle={Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence}, | |
| publisher={Association for the Advancement of Artificial Intelligence}, | |
| year={2023}, | |
| month={February} | |
| } | |
| ``` |