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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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21#
發(fā)表于 2025-3-25 03:42:27 | 只看該作者
Omair Bhatti,Michael Barz,Daniel SonntagEinbettung in die Literaturkultur ihrer Zeit. Im Fokus stehen Oskar Baum, Karl Brand, Max Brod, Ernst Feigl, Milena Jesenská, Paul Kornfeld, Alfred Kubin, Jizchak L?wy, Otto Pick, Miriam Singer, Johannes Urzidil, Melchior Vischer, Ernst Wei? und Franz Werfel..978-3-662-67640-0
22#
發(fā)表于 2025-3-25 10:34:41 | 只看該作者
23#
發(fā)表于 2025-3-25 13:17:33 | 只看該作者
https://doi.org/10.1007/978-3-031-15791-2artificial intelligence; computer hardware; computer networks; computer vision; data mining; databases; fo
24#
發(fā)表于 2025-3-25 17:39:48 | 只看該作者
25#
發(fā)表于 2025-3-25 21:26:42 | 只看該作者
26#
發(fā)表于 2025-3-26 02:04:33 | 只看該作者
KI 2022: Advances in Artificial Intelligence978-3-031-15791-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
27#
發(fā)表于 2025-3-26 05:59:42 | 只看該作者
,Assessing the?Performance Gain on?Retail Article Categorization at?the?Expense of?Explainability ansolid low-resource baseline for deep learning-based models, on two different retail article categorization datasets; and we finally discuss the suitability of the different presented models when they need to be deployed considering not only their classification performance but also their implied resource costs and explainability aspects.
28#
發(fā)表于 2025-3-26 09:01:28 | 只看該作者
Unsupervised Alignment of Distributional Word Embeddings,ed manner. We evaluate our method on the problem of unsupervised word translation, by aligning word embeddings trained on monolingual data. We present empirical evidence to demonstrate the validity of our approach to the bilingual lexicon induction task across several language pairs.
29#
發(fā)表于 2025-3-26 13:04:10 | 只看該作者
,NeuralPDE: Modelling Dynamical Systems from?Data,he NeuralPDE Model, which explicitly takes into account the fact that the data is governed by differential equations. We show in several experiments on toy and real-world data that our model consistently outperforms state-of-the-art models used to learn dynamical systems.
30#
發(fā)表于 2025-3-26 17:32:05 | 只看該作者
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