E-LIB Suche - Ergebnisse für: van Krieken, Emile

1

Refining neural network predictions using background knowle..:

Daniele, Alessandro ; van Krieken, Emile ; Serafini, Luciano.
Machine Learning. 112 (2023) 9 - p. 3293-3331 , 2023

Link: https://doi.org/10.1007/..

2

Analyzing Differentiable Fuzzy Logic Operators:

van Krieken, Emile ; Acar, Erman ; van Harmelen, Frank
Artificial Intelligence. 302 (2022) - p. 103602 , 2022

Link: https://doi.org/10.1016/..

3

Analysis of Measure-Valued Derivatives in a Reinforcement L..:

, In: 2022 Winter Simulation Conference (WSC),

van den Houten, Kim ; van Krieken, Emile ; Heidergott, Bernd - p. 2736-2747 , 2022

Link: https://doi.org/10.1109/..

4

Optimisation in Neurosymbolic Learning Systems:

van Krieken, Emile
http://arxiv.org/abs/2401.10819. , 2024

Link: http://arxiv.org/abs/240..

5

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Ge..:

Thanapalasingam, Thiviyan ; van Krieken, Emile ; Bloem, Peter.
http://arxiv.org/abs/2307.06698. , 2023

Link: http://arxiv.org/abs/230..

6

GRAPES: Learning to Sample Graphs for Scalable Graph Neural..:

Younesian, Taraneh ; Thanapalasingam, Thiviyan ; van Krieken, Emile..
http://arxiv.org/abs/2310.03399. , 2023

Link: http://arxiv.org/abs/231..

7

Refining neural network predictions using background knowle..:

Daniele, Alessandro ; van Krieken, Emile ; Serafini, Luciano.
http://arxiv.org/abs/2206.04976. , 2022

Link: http://arxiv.org/abs/220..

8

Prompting as Probing: Using Language Models for Knowledge B..:

Alivanistos, Dimitrios ; Santamaría, Selene Báez ; Cochez, Michael...
http://arxiv.org/abs/2208.11057. , 2022

Link: http://arxiv.org/abs/220..

9

A-NeSI: A Scalable Approximate Method for Probabilistic Neu..:

van Krieken, Emile ; Thanapalasingam, Thiviyan ; Tomczak, Jakub M..
http://arxiv.org/abs/2212.12393. , 2022

Link: http://arxiv.org/abs/221..

10

Storchastic: A Framework for General Stochastic Automatic D..:

van Krieken, Emile ; Tomczak, Jakub M ; Teije, Annette ten
http://arxiv.org/abs/2104.00428. , 2021

Link: http://arxiv.org/abs/210..

11

Analyzing Differentiable Fuzzy Implications:

Krieken, Emile van ; Acar, Erman ; Harmelen, Frank van
Krieken , E V , Acar , E & Harmelen , F V 2020 , Analyzing Differentiable Fuzzy Implications . in D Calvanese , E Erdem & M Thielscher (eds) , KR2020 : Proceedings of the 17th Conference on Principles of Knowledge Representation and Reasoning. Rhodes, Greece. September 12-18, 2020 . KR Proceedings : Proceedings of the xxth Conference on Principles of Knowledge Representation and Reasoning , vol. 2020-17th , IJCAI Organization , pp. 893-903 . https://doi.org/10.24963/kr.2020/92. , 2020

Link: https://research.vu.nl/e..

12

Analyzing Differentiable Fuzzy Implications:

van Krieken, Emile ; Acar, Erman ; van Harmelen, Frank
http://arxiv.org/abs/2006.03472. , 2020

Link: http://arxiv.org/abs/200..

13

Analyzing Differentiable Fuzzy Logic Operators:

van Krieken, Emile ; Acar, Erman ; van Harmelen, Frank
http://arxiv.org/abs/2002.06100. , 2020

Link: http://arxiv.org/abs/200..

14

Semi-Supervised Learning using Differentiable Reasoning:

van Krieken, Emile ; Acar, Erman ; van Harmelen, Frank
http://arxiv.org/abs/1908.04700. , 2019

Link: http://arxiv.org/abs/190..

15

Semi-Supervised Learning using Differentiable Reasoning:

van Krieken, Emile ; Acar, E ; van Harmelen, Frank
van Krieken , E , Acar , E & van Harmelen , F 2019 , ' Semi-Supervised Learning using Differentiable Reasoning ' , Journal of Applied Logic , vol. 6 , no. 4 , pp. 633-651 .. , 2019

Link: https://research.vu.nl/e..