Interpretable Models via Pairwise Permutations Algorithm
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2021 |
Maasland, Troy |
Migrating Models: A Decentralized View on Federated Learning
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2021 |
Kiss, Péter |
Towards Precomputed 1D-Convolutional Layers for Embedded FPGAs
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2021 |
Einhaus, Lukas |
Towards Mining Generalized Patterns from RDF Data and a Domain Ontology
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2021 |
Martin, Tomas |
Graph Homomorphism Features: Why Not Sample?
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2021 |
Beaujean, Paul |
Continuous-Discrete Recurrent Kalman Networks for Irregular Time Series
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2021 |
Schirmer, Mona |
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition
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2021 |
Nauta, Meike |
Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification
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2021 |
Pluciński, Kamil |
Algorithmic Factors Influencing Bias in Machine Learning
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2021 |
Blanzeisky, William |
Towards Stochastic Fault-Tolerant Control Using Precision Learning and Active Inference
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2021 |
Baioumy, Mohamed |
On the Convergence of DEM’s Linear Parameter Estimator
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2021 |
Meera, Ajith Anil |
Robot Localization and Navigation Through Predictive Processing Using LiDAR
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2021 |
Burghardt, Daniel |
Ideas Worth Spreading: A Free Energy Proposal for Cumulative Cultural Dynamics
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2021 |
Kastel, Natalie |
On the Transferability of Neural Models of Morphological Analogies
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2021 |
Alsaidi, Safa |
Demystifying Graph Neural Network Explanations
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2021 |
Himmelhuber, Anna |
Behavior of k-NN as an Instance-Based Explanation Method
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2021 |
Yadav, Chhavi |
Optimized Federated Learning on Class-Biased Distributed Data Sources
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2021 |
Mou, Yongli |
Splitting Algorithms for Federated Learning
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2021 |
Malekmohammadi, Saber |
Approaches to Uncertainty Quantification in Federated Deep Learning
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2021 |
Linsner, Florian |
SPNC: Fast Sum-Product Network Inference
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2021 |
Sommer, Lukas |