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Anna Krause

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2020 – today

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2024
[c14]
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Julian Tritscher, Maximilian Wolf, Anna Krause, Andreas Hotho, Daniel Schlör:
Data Generation for Explainable Occupational Fraud Detection. KI 2024: 246-259
[c13]
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Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause:
GrINd: Grid Interpolation Network for Scattered Observations. ECML/PKDD (7) 2024: 177-193
[c12]
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Julian Tritscher, Philip Lissmann, Maximilian Wolf, Anna Krause, Andreas Hotho, Daniel Schlör:
Generative Inpainting for Shapley-Value-Based Anomaly Explanation. xAI (1) 2024: 230-243
[i10]
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  - journals/corr/abs-2403-18438
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Pascal Janetzky, Florian Gallusser, Simon Hentschel, Andreas Hotho, Anna Krause:
Global Vegetation Modeling with Pre-Trained Weather Transformers. CoRR abs/2403.18438 (2024)
[i9]
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  - journals/corr/abs-2403-19570
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Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause:
GrINd: Grid Interpolation Network for Scattered Observations. CoRR abs/2403.19570 (2024)
2023
[j3]
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  - journals/datamine/SteiningerAZKPH23
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Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho:
ConvMOS: climate model output statistics with deep learning. Data Min. Knowl. Discov. 37(1): 136-166 (2023)
[j2]
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  - journals/frai/TritscherKH23
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Julian Tritscher, Anna Krause, Andreas Hotho:
Feature relevance XAI in anomaly detection: Reviewing approaches and challenges. Frontiers Artif. Intell. 6 (2023)
[c11]
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  - conf/iwssip/JanetzkySKH23
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Pascal Janetzky, Melanie Schaller, Anna Krause, Andreas Hotho:
Swarming Detection in Smart Beehives Using Auto Encoders for Audio Data. IWSSIP 2023: 1-5
[c10]
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Pascal Janetzky, Philip Lissmann, Andreas Hotho, Anna Krause:
Automatic Speech Detection on a Smart Beehive's Raspberry Pi. LWDA 2023: 424-429
[c9]
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Andrzej Dulny, Andreas Hotho, Anna Krause:
DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data. ECML/PKDD (1) 2023: 438-455
[i8]
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  - journals/corr/abs-2306-05805
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Andrzej Dulny, Andreas Hotho, Anna Krause:
DynaBench: A benchmark dataset for learning dynamical systems from low-resolution data. CoRR abs/2306.05805 (2023)
[i7]
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  - journals/corr/abs-2306-14511
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Paul Heinisch, Andrzej Dulny, Anna Krause, Andreas Hotho:
TaylorPDENet: Learning PDEs from non-grid Data. CoRR abs/2306.14511 (2023)
2022
[c8]
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Andrzej Dulny, Andreas Hotho, Anna Krause:
NeuralPDE: Modelling Dynamical Systems from Data. KI 2022: 75-89
[c7]
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Julian Tritscher, Daniel Schlör, Fabian Gwinner, Anna Krause, Andreas Hotho:
Towards Explainable Occupational Fraud Detection. PKDD/ECML Workshops (2) 2022: 79-96
[i6]
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  - journals/corr/abs-2206-04460
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Julian Tritscher, Fabian Gwinner, Daniel Schlör, Anna Krause, Andreas Hotho:
Open ERP System Data For Occupational Fraud Detection. CoRR abs/2206.04460 (2022)
[i5]
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  - journals/corr/abs-2207-03119
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Padraig Davidson, Michael Steininger, André Huhn, Anna Krause, Andreas Hotho:
Semi-unsupervised Learning for Time Series Classification. CoRR abs/2207.03119 (2022)
2021
[j1]
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  - journals/ml/SteiningerKDKH21
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Michael Steininger, Konstantin Kobs, Padraig Davidson, Anna Krause, Andreas Hotho:
Density-based weighting for imbalanced regression. Mach. Learn. 110(8): 2187-2211 (2021)
[c6]
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  - conf/cig/TritscherKSGMH21
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Julian Tritscher, Anna Krause, Daniel Schlör, Fabian Gwinner, Sebastian von Mammen, Andreas Hotho:
A financial game with opportunities for fraud. CoG 2021: 1-5
[c5]
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Pascal Janetzky, Padraig Davidson, Michael Steininger, Anna Krause, Andreas Hotho:
Detecting Presence Of Speech In Acoustic Data Obtained From Beehives. DCASE 2021: 26-30
[c4]
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  - conf/ki/DavidsonBSKH21
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Padraig Davidson, Florian Buckermann, Michael Steininger, Anna Krause, Andreas Hotho:
Semi-unsupervised Learning: An In-depth Parameter Analysis. KI 2021: 51-66
[i4]
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  - journals/corr/abs-2110-03945
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Padraig Davidson, Michael Steininger, Florian Lautenschlager, Anna Krause, Andreas Hotho:
Anomaly Detection in Beehives: An Algorithm Comparison. CoRR abs/2110.03945 (2021)
[i3]
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  - journals/corr/abs-2111-07671
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Andrzej Dulny, Andreas Hotho, Anna Krause:
NeuralPDE: Modelling Dynamical Systems from Data. CoRR abs/2111.07671 (2021)
2020
[c3]
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  - conf/icpr/KobsSSKBPH20
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Konstantin Kobs, Christian Schäfer, Michael Steininger, Anna Krause, Roland Baumhauer, Heiko Paeth, Andreas Hotho:
Semi-Supervised Learning for Grain Size Distribution Interpolation. ICPR Workshops (6) 2020: 34-44
[c2]
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  - conf/pkdd/SchlorRKH20
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Daniel Schlör, Markus Ring, Anna Krause, Andreas Hotho:
Financial Fraud Detection with Improved Neural Arithmetic Logic Units. MIDAS@PKDD/ECML 2020: 40-54
[c1]
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  - conf/sensornets/DavidsonSLKKH20
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Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho:
Anomaly Detection in Beehives using Deep Recurrent Autoencoders. SENSORNETS 2020: 142-149
[i2]
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  - journals/corr/abs-2003-04576
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Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho:
Anomaly Detection in Beehives using Deep Recurrent Autoencoders. CoRR abs/2003.04576 (2020)
[i1]
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  - journals/corr/abs-2012-10394
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Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho:
Deep Learning for Climate Model Output Statistics. CoRR abs/2012.10394 (2020)

2010 – 2019

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2019
[b1]
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  - phd/dnb/Krause19a
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Anna Krause:
Variation-aware behavioural modelling using support vector machines and affine arithmetic. University of Hanover, Hannover, Germany, 2019

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