Michael Siebers
Cited by
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Computer models solving intelligence test problems: Progress and implications
J Hernández-Orallo, F Martínez-Plumed, U Schmid, M Siebers, DL Dowe
Artificial Intelligence 230, 74-107, 2016
Enriching Visual with Verbal Explanations for Relational Concepts--Combining LIME with Aleph
J Rabold, H Deininger, M Siebers, U Schmid
arXiv preprint arXiv:1910.01837, 2019
Explaining black-box classifiers with ILP–empowering LIME with Aleph to approximate non-linear decisions with relational rules
J Rabold, M Siebers, U Schmid
International Conference on Inductive Logic Programming, 105-117, 2018
Problems of video-based pain detection in patients with dementia: a road map to an interdisciplinary solution
M Kunz, D Seuss, T Hassan, JU Garbas, M Siebers, U Schmid, ...
BMC Geriatrics 17 (1), 33, 2017
Characterizing facial expressions by grammars of action unit sequences–A first investigation using ABL
M Siebers, U Schmid, D Seuß, M Kunz, S Lautenbacher
Information Sciences 329, 866-875, 2016
Semi-analytic natural number series induction
M Siebers, U Schmid
KI 2012: Advances in Artificial Intelligence, 249-252, 2012
Please delete that! Why should I?
M Siebers, U Schmid
KI-Künstliche Intelligenz 33 (1), 35-44, 2019
Applying Grammar Inference To Identify Generalized Patterns of Facial Expressions of Pain.
U Schmid, M Siebers, D Seuß, M Kunz, S Lautenbacher
ICGI, 183-188, 2012
Intentional Forgetting in Socio-Digital Work Systems
T Ellwart, AS Ulfert, CH Antoni, J Becker, C Frings, K Göbel, G Hertel, ...
AIS Transactions on Enterprise Systems 4 (1), 2019
A cognitive model for predicting esthetical judgements as similarity to dynamic prototypes
U Schmid, M Siebers, J Folger, S Schineller, D Seuß, M Raab, CC Carbon, ...
Cognitive Systems Research 24, 72-79, 2013
On the Relevance of Sequence Information for Decoding Facial Expressions of Pain and Disgust?: An Avatar Study
M Siebers, T Engelbrecht, U Schmid
7th Workshop Emotion & Computing -- Current Research and Future Impact, 3-9, 2013
A Cognitive Model For Predicting Aesthetical Judgements As Similarity to Dynamic Prototypes
U Schmid, M Siebers, J Folger, S Schineller, D Seuß, M Raab, CC Carbon, ...
11th International Conference on Cognitive Modeling, 13-18, 2012
Intentional Forgetting in Artificial Intelligence Systems: Perspectives and Challenges
IJ Timm, S Staab, M Siebers, C Schon, U Schmid, K Sauerwald, L Reuter, ...
Joint German/Austrian Conference on Artificial Intelligence (Künstliche …, 2018
Requirements for a companion system to support identifying irrelevancy
M Siebers, K Gobel, C Niessen, U Schmid
2017 International Conference on Companion Technology (ICCT), 1-2, 2017
A Psychonic Approach to the Design of a Cognitive Companion Supporting Intentional Forgetting
M Siebers, U Schmid, K Göbel, C Niessen
6. Workshop Kognitive Systeme: Mensch, Teams, Systeme und Automaten, 2017
Analogical problem solving: insights from verbal reports
L Gralla, T Tenbrink, M Siebers, U Schmid
Proceedings of the 34th Annual Conference of the Cognitive Science Society …, 2012
Time to Forget
C Niessen, K Göbel, M Siebers, U Schmid
Zeitschrift für Arbeits-und Organisationspsychologie A&O, 2019
Classifying Facial Pain Expressions Individual Classifiers vs. Global Classifiers
M Siebers, M Kunz, S Lautenbacher, U Schmid
4th Workshop on Emotion and Computing - Current Research and Future Impact …, 2009
A process framework for inducing and explaining Datalog theories
M Gromowski, M Siebers, U Schmid
Advances in Data Analysis and Classification 14 (4), 821-835, 2020
Was the Year 2000 a Leap Year? Step-Wise Narrowing Theories with Metagol
M Siebers, U Schmid
International Conference on Inductive Logic Programming, 141-156, 2018
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