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Christoph Schorn
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Year
Accurate neuron resilience prediction for a flexible reliability management in neural network accelerators
C Schorn, A Guntoro, G Ascheid
2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), 979-984, 2018
642018
SELD-TCN: Sound event localization & detection via temporal convolutional networks
K Guirguis, C Schorn, A Guntoro, S Abdulatif, B Yang
2020 28th European Signal Processing Conference (EUSIPCO), 16-20, 2021
632021
Efficient on-line error detection and mitigation for deep neural network accelerators
C Schorn, A Guntoro, G Ascheid
Computer Safety, Reliability, and Security: 37th International Conference …, 2018
512018
An efficient bit-flip resilience optimization method for deep neural networks
C Schorn, A Guntoro, G Ascheid
2019 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2019
502019
Automated design of error-resilient and hardware-efficient deep neural networks
C Schorn, T Elsken, S Vogel, A Runge, A Guntoro, G Ascheid
Neural Computing and Applications 32, 18327-18345, 2020
462020
Facer: A universal framework for detecting anomalous operation of deep neural networks
C Schorn, L Gauerhof
2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020
122020
Efficient stochastic inference of bitwise deep neural networks
S Vogel, C Schorn, A Guntoro, G Ascheid
arXiv preprint arXiv:1611.06539, 2016
122016
Fault Injectors for TensorFlow: evaluation of the impact of random hardware faults on deep CNNs
M Beyer, A Morozov, E Valiev, C Schorn, L Gauerhof, K Ding, K Janschek
arXiv preprint arXiv:2012.07037, 2020
112020
Bayesian Model for Trustworthiness Analysis of Deep Learning Classifiers.
A Morozov, E Valiev, M Beyer, K Ding, L Gauerhof, C Schorn
AISafety@ IJCAI, 2020
52020
Guaranteed compression rate for activations in cnns using a frequency pruning approach
S Vogel, C Schorn, A Guntoro, G Ascheid
2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), 296-299, 2019
52019
Method for calculating an output of a neural network
C Schorn, S Vogel
US Patent 11,301,749, 2022
42022
Automated hardening of deep neural network architectures
M Beyer, C Schorn, T Fabarisov, A Morozov, K Janschek
ASME International Mechanical Engineering Congress and Exposition 85697 …, 2021
42021
Considering reliability of deep learning function to boost data suitability and anomaly detection
L Gauerhof, Y Hagiwara, C Schorn, M Trapp
2020 IEEE International Symposium on Software Reliability Engineering …, 2020
22020
Inference calculation for neural networks with protection against memory errors
A Guntoro, C Schorn, J Pletinckx, LL Ecco, S Vogel
US Patent App. 17/798,978, 2023
12023
Method and device for verifying a neuron function in a neural network
A Guntoro, A Runge, C Schorn, S Vogel, J Topp, J Schirmer
US Patent 11,593,232, 2023
12023
Method, device, and computer program for creating training data in a vehicle
C Schorn, L Gauerhof
US Patent App. 17/658,323, 2022
12022
Method and device for operating a neural network in a memory-efficient manner
A Guntoro, A Runge, C Schorn, J Topp, S Vogel, J Schirmer
US Patent 11,715,019, 2023
2023
Selective deactivation of processing units for artificial neural networks
J Schirmer, A Guntoro, A Runge, C Schorn, J Topp, S Vogel
US Patent 11,698,672, 2023
2023
Method, device, and computer program for an uncertainty assessment of an image classification
C Schorn, L Gauerhof
US Patent App. 17/698,766, 2022
2022
Method and device for correcting erroneous neuron functions in a neural network
A Guntoro, C Schorn, J Pletinckx, LL Ecco, S Vogel
US Patent App. 17/328,761, 2021
2021
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