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      TorchCP: A Library for Conformal Prediction based on PyTorch

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          Abstract

          TorchCP is a Python toolbox for conformal prediction research on deep learning models. It contains various implementations for posthoc and training methods for classification and regression tasks (including multi-dimension output). TorchCP is built on PyTorch (Paszke et al., 2019) and leverages the advantages of matrix computation to provide concise and efficient inference implementations. The code is licensed under the LGPL license and is open-sourced at \(\href{https://github.com/ml-stat-Sustech/TorchCP}{\text{this https URL}}\).

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          Author and article information

          Journal
          19 February 2024
          Article
          2402.12683
          7f69a61b-11bd-4c92-9455-250a78fbb462

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          cs.LG cs.CV math.ST stat.TH

          Computer vision & Pattern recognition,Artificial intelligence,Statistics theory

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