We show that architectures from the machine learning domain of continual learning can help language models to procedurally learn facts about the world.
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We design a multi-agent simulation that can produce company data that also contains hidden fraud cases.
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We rigorously evaluate commonly used approaches that explain the decisions of network attack detection systems.
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In our work we propose a method for learning explicit representations of PDEs from non-grid data
MehrBigData@Geo geht in die zweite Runde!
04.07.2023
Mehr kooperierende Betriebe, höhere Förderung, ein neuer Partner innerhalb der Uni: BigData@Geo geht in die zweite Runde und will mit Hilfe von Klimadaten konkrete Handlungsempfehlungen für Unternehmen mit Naturbezug erstellen.
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In our work we present a benchmark dataset for learning forecasts of dynamical systems on non-grid structured data
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In our paper we propose a method allowing the comparison of human behaviour across behavioural networks with different properties.
MehrDr Anna Krause is co-organizing the workshop "Neuro-Explicit AI and Expert-Informed Machine Learning for Engineering and Physical Sciences (ExML)" at ECMLPKDD 2023.
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In our paper, we conduct an initial study to investigate the use of audio data from the We4Bee project in detecting bee swarming.
MehrCAIDAS at the ai.bay 2023
28.02.2023
