Anna Krause

32 papers C 1Misc 3Journal 15Unranked 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
Exploring Design Choices for Autoregressive Deep Learning Climate Models.
CoRR
Florian Gallusser, Simon Hentschel, Anna Krause, Andreas Hotho
2025 J jnl
Physical knowledge improves prediction of EM Fields.
CoRR
Andrzej Dulny, Farzad Jabbarigargari, Andreas Hotho, Laura Maria Schreiber, Maxim Terekhov, Anna Krause
2025 — conf
TaylorNet: Learning PDEs from Non-Grid Data.
ML-DE
Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause
2024 Misc conf
Data Generation for Explainable Occupational Fraud Detection.
KI
Julian Tritscher, Maximilian Wolf, Anna Krause, Andreas Hotho, Daniel Schlör
2024 — conf
Generative Inpainting for Shapley-Value-Based Anomaly Explanation.
xAI (1)
Julian Tritscher, Philip Lissmann, Maximilian Wolf, Anna Krause, Andreas Hotho, Daniel Schlör
2024 J jnl
Global Vegetation Modeling with Pre-Trained Weather Transformers.
CoRR
Pascal Janetzky, Florian Gallusser, Simon Hentschel, Andreas Hotho, Anna Krause
2024 — conf
GrINd: Grid Interpolation Network for Scattered Observations.
ECML/PKDD (7)
Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause
2024 J jnl
GrINd: Grid Interpolation Network for Scattered Observations.
CoRR
Andrzej Dulny, Paul Heinisch, Andreas Hotho, Anna Krause
2023 — conf
Automatic Speech Detection on a Smart Beehive's Raspberry Pi.
LWDA
Pascal Janetzky, Philip Lissmann, Andreas Hotho, Anna Krause
2023 J jnl
ConvMOS: climate model output statistics with deep learning.
Data Min. Knowl. Discov.
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho
2023 — conf
DynaBench: A Benchmark Dataset for Learning Dynamical Systems from Low-Resolution Data.
ECML/PKDD (1)
Andrzej Dulny, Andreas Hotho, Anna Krause
2023 J jnl
DynaBench: A benchmark dataset for learning dynamical systems from low-resolution data.
CoRR
Andrzej Dulny, Andreas Hotho, Anna Krause
2023 J jnl
Feature relevance XAI in anomaly detection: Reviewing approaches and challenges.
Frontiers Artif. Intell.
Julian Tritscher, Anna Krause, Andreas Hotho
2023 — conf
Occupational Fraud Detection Through Agent-Based Data Generation.
PKDD/ECML Workshops (5)
Julian Tritscher, Alexander Roos, Daniel Schlör, Andreas Hotho, Anna Krause
2023 — conf
Swarming Detection in Smart Beehives Using Auto Encoders for Audio Data.
IWSSIP
Pascal Janetzky, Melanie Schaller, Anna Krause, Andreas Hotho
2023 J jnl
TaylorPDENet: Learning PDEs from non-grid Data.
CoRR
Paul Heinisch, Andrzej Dulny, Anna Krause, Andreas Hotho
2022 Misc conf
NeuralPDE: Modelling Dynamical Systems from Data.
KI
Andrzej Dulny, Andreas Hotho, Anna Krause
2022 J jnl
Open ERP System Data For Occupational Fraud Detection.
CoRR
Julian Tritscher, Fabian Gwinner, Daniel Schlör, Anna Krause, Andreas Hotho
2022 J jnl
Semi-unsupervised Learning for Time Series Classification.
CoRR
Padraig Davidson, Michael Steininger, André Huhn, Anna Krause, Andreas Hotho
2022 — conf
Towards Explainable Occupational Fraud Detection.
PKDD/ECML Workshops (2)
Julian Tritscher, Daniel Schlör, Fabian Gwinner, Anna Krause, Andreas Hotho
2021 C conf
A financial game with opportunities for fraud.
CoG
Julian Tritscher, Anna Krause, Daniel Schlör, Fabian Gwinner, Sebastian von Mammen, Andreas Hotho
2021 J jnl
Anomaly Detection in Beehives: An Algorithm Comparison.
CoRR
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Anna Krause, Andreas Hotho
2021 J jnl
Density-based weighting for imbalanced regression.
Mach. Learn.
Michael Steininger, Konstantin Kobs, Padraig Davidson, Anna Krause, Andreas Hotho
2021 — conf
Detecting Presence Of Speech In Acoustic Data Obtained From Beehives.
DCASE
Pascal Janetzky, Padraig Davidson, Michael Steininger, Anna Krause, Andreas Hotho
2021 J jnl
NeuralPDE: Modelling Dynamical Systems from Data.
CoRR
Andrzej Dulny, Andreas Hotho, Anna Krause
2021 Misc conf
Semi-unsupervised Learning: An In-depth Parameter Analysis.
KI
Padraig Davidson, Florian Buckermann, Michael Steininger, Anna Krause, Andreas Hotho
2020 — conf
Anomaly Detection in Beehives using Deep Recurrent Autoencoders.
SENSORNETS
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho
2020 J jnl
Anomaly Detection in Beehives using Deep Recurrent Autoencoders.
CoRR
Padraig Davidson, Michael Steininger, Florian Lautenschlager, Konstantin Kobs, Anna Krause, Andreas Hotho
2020 J jnl
Deep Learning for Climate Model Output Statistics.
CoRR
Michael Steininger, Daniel Abel, Katrin Ziegler, Anna Krause, Heiko Paeth, Andreas Hotho
2020 — conf
Financial Fraud Detection with Improved Neural Arithmetic Logic Units.
MIDAS@PKDD/ECML
Daniel Schlör, Markus Ring, Anna Krause, Andreas Hotho
2020 — conf
Semi-Supervised Learning for Grain Size Distribution Interpolation.
ICPR Workshops (6)
Konstantin Kobs, Christian Schäfer, Michael Steininger, Anna Krause, Roland Baumhauer, Heiko Paeth, Andreas Hotho
2019 — —
Variation-aware behavioural modelling using support vector machines and affine arithmetic.
Anna Krause