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A Survey on Uncertainty Toolkits for Deep Learning


May 02, 2022
Maximilian Pintz, Joachim Sicking, Maximilian Poretschkin, Maram Akila

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* Accepted at the ICLR 2022 workshop "Setting up ML Evaluation Standards to Accelerate Progress" 

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A Novel Regression Loss for Non-Parametric Uncertainty Optimization


Jan 07, 2021
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel

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* Accepted at the 3rd Symposium on Advances in Approximate Bayesian Inference (AABI), code is available on: https://github.com/fraunhofer-iais/second-moment-loss. arXiv admin note: substantial text overlap with arXiv:2012.12687 

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Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties


Dec 23, 2020
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel

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* Code is available on: https://github.com/fraunhofer-iais/second-moment-loss 

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DenseHMM: Learning Hidden Markov Models by Learning Dense Representations


Dec 17, 2020
Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz

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* Accepted at LMRL workshop at NeurIPS 2020. Code is available on: https://github.com/fraunhofer-iais/dense-hmm 

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