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- Goddard Space Flight CenterUS21 papers
- Centre National de la Recherche ScientifiqueFR18 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR18 papers
- Astrophysique, Instrumentation et ModélisationFR17 papers
- Max Planck Institute for Radio AstronomyDE17 papers
- Universities Space Research AssociationUS17 papers
- National Institute for AstrophysicsIT16 papers
- University of Maryland, College ParkUS16 papers
- University of PaduaIT16 papers
- University of Rome Tor VergataIT16 papers
- CEA Paris-SaclayFR15 papers
- Friedrich-Alexander-Universität Erlangen-NürnbergDE15 papers
6 papers · 1 filter
Solving Quantified Modal Logic Problems by Translation to Classical Logics
Alexander Steen, Geoff Sutcliffe, Christoph Benzmüller
This article describes an evaluation of Automated Theorem Proving (ATP) systems on problems taken from the QMLTP library of first-order modal logic problems. Principally, the probl…
CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition
Ines Rieger, Jaspar Pahl, Bettina Finzel +1
Neural networks are widely adopted, yet the integration of domain knowledge is still underutilized. We propose to integrate domain knowledge about co-occurring facial movements as…
Who Finds the Short Proof? An Exploration of Variants of Boolos' Curious Inference using Higher-order Automated Theorem Provers
Christoph Benzmüller, David Fuenmayor, Alexander Steen +1
This paper reports on an exploration of Boolos' Curious Inference, using higher-order automated theorem provers (ATPs). Surprisingly, only suitable shorthand notations had to be pr…
Explanatory machine learning for sequential human teaching
Lun Ai, Johannes Langer, Stephen H. Muggleton +1
The topic of comprehensibility of machine-learned theories has recently drawn increasing attention. Inductive Logic Programming (ILP) uses logic programming to derive logic theorie…
Analysing Opportunity Cost of Care Work using Mixed Effects Random Forests under Aggregated Auxiliary Data
Patrick Krennmair, Nora Würz, Timo Schmid
Evidence-based policy-making requires reliable, spatially disaggregated indicators. The framework of mixed effects random forests leverages the advantages of random forests and hie…
Flexible domain prediction using mixed effects random forests
Patrick Krennmair, Timo Schmid
This paper promotes the use of random forests as versatile tools for estimating spatially disaggregated indicators in the presence of small area-specific sample sizes. Small area e…