Emile van Krieken

According to our database, Emile van Krieken authored at least 13 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts.

Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Antonio Vergari, Andrea Passerini, Stefano Teso

CoRR, 2024

Optimisation in Neurosymbolic Learning Systems.

Emile van Krieken

CoRR, 2024

2023

Refining neural network predictions using background knowledge.

Alessandro Daniele, Emile van Krieken, Luciano Serafini, Frank van Harmelen

Mach. Learn., September, 2023

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

Taraneh Younesian, Thiviyan Thanapalasingam, Emile van Krieken, Daniel Daza, Peter Bloem

CoRR, 2023

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation.

Thiviyan Thanapalasingam, Emile van Krieken, Peter Bloem, Paul Groth

CoRR, 2023

A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference.

Emile van Krieken, Thiviyan Thanapalasingam, Jakub M. Tomczak, Frank van Harmelen, Annette ten Teije

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Analyzing Differentiable Fuzzy Logic Operators.

Emile van Krieken, Erman Acar, Frank van Harmelen

Artif. Intell., 2022

Analysis of Measure-Valued Derivatives in a Reinforcement Learning Actor-Critic Framework.

Kim van den Houten, Emile van Krieken, Bernd Heidergott

Proceedings of the Winter Simulation Conference, 2022

Prompting as Probing: Using Language Models for Knowledge Base Construction.

Dimitrios Alivanistos, Selene Baez Santamaría, Michael Cochez, Jan-Christoph Kalo, Emile van Krieken, Thiviyan Thanapalasingam

Proceedings of the Semantic Web Challenge on Knowledge Base Construction from Pre-trained Language Models 2022 co-located with the 21st International Semantic Web Conference (ISWC2022), 2022

2021

Storchastic: A Framework for General Stochastic Automatic Differentiation.

Emile van Krieken, Jakub M. Tomczak, Annette ten Teije

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Analyzing Differentiable Fuzzy Implications.

Emile van Krieken, Erman Acar, Frank van Harmelen

Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, 2020

2019

Semi-supervised Learning using Differentiable Reasoning.

Emile van Krieken, Erman Acar, Frank van Harmelen

FLAP, 2019

2018

Benefits of Social Learning in Physical Robots.

Jacqueline Heinerman, Bart Bussmann, Rick Groenendijk, Emile van Krieken, Jesper Slik, Alessandro Tezza, Evert Haasdijk, A. E. Eiben

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018