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Titlebook: KI 2022: Advances in Artificial Intelligence; 45th German Conferen Ralph Bergmann,Lukas Malburg,Ingo J. Timm Conference proceedings 2022 Th

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31#
發(fā)表于 2025-3-26 21:51:55 | 只看該作者
32#
發(fā)表于 2025-3-27 02:05:31 | 只看該作者
,Leveraging Implicit Gaze-Based User Feedback for?Interactive Machine Learning,e learning system by observing its eye movements and facial expressions. In this paper, we describe our approach for modelling user disagreement and discuss how such a model could be used for triggering user feedback requests in the context of interactive machine learning.
33#
發(fā)表于 2025-3-27 06:42:38 | 只看該作者
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發(fā)表于 2025-3-27 10:23:13 | 只看該作者
35#
發(fā)表于 2025-3-27 17:37:25 | 只看該作者
36#
發(fā)表于 2025-3-27 19:37:39 | 只看該作者
,PEBAM: A Profile-Based Evaluation Method for?Bias Assessment on?Mixed Datasets,e proposed profile-based evaluation method for bias assessment on mixed datasets (PEBAM) can reveal forms of bias towards profiles expressed by the dataset that are undetected when using individual- or group-bias metrics alone.
37#
發(fā)表于 2025-3-27 22:50:27 | 只看該作者
,Deep Neural Networks for?Geometric Shape Deformation,at can be easily fed into a neural network. In this paper, we demonstrate how deep SDF neural networks can be used to precisely predict the deformation of a material after the application of a specific force. The model is trained using a set of custom finite element simulations in order to generalize to unseen forces.
38#
發(fā)表于 2025-3-28 03:30:14 | 只看該作者
39#
發(fā)表于 2025-3-28 10:00:31 | 只看該作者
Conference proceedings 2022ID-19 the conference was held virtually..The chapter "Dynamically Self-Adjusting Gaussian Processes for Data Stream Modelling" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..
40#
發(fā)表于 2025-3-28 10:52:35 | 只看該作者
0302-9743 Due to COVID-19 the conference was held virtually..The chapter "Dynamically Self-Adjusting Gaussian Processes for Data Stream Modelling" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..978-3-031-15790-5978-3-031-15791-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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