Emile van Krieken

About Emile van Krieken

Emile van Krieken, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Vrije Universiteit Amsterdam, specializes in the field of Neurosymbolic AI, Machine Learning, Optimization.

His recent articles reflect a diverse array of research interests and contributions to the field:

ULLER: A Unified Language for Learning and Reasoning

On the Independence Assumption in Neurosymbolic Learning

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts

A-nesi: A scalable approximate method for probabilistic neurosymbolic inference

Optimisation in Neurosymbolic Learning Systems

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks

Refining neural network predictions using background knowledge

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation

Emile van Krieken Information

University

Position

PhD at KRR and CI groups

Citations(all)

213

Citations(since 2020)

213

Cited By

25

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Emile van Krieken Skills & Research Interests

Neurosymbolic AI

Machine Learning

Optimization

Top articles of Emile van Krieken

Title

Journal

Author(s)

Publication Date

ULLER: A Unified Language for Learning and Reasoning

arXiv preprint arXiv:2405.00532

Emile van Krieken

Samy Badreddine

Robin Manhaeve

Eleonora Giunchiglia

2024/5/1

On the Independence Assumption in Neurosymbolic Learning

ICML 2024

Emile van Krieken

Pasquale Minervini

Edoardo M Ponti

Antonio Vergari

2024/4/12

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts

arXiv preprint arXiv:2402.12240

Emanuele Marconato

Samuele Bortolotti

Emile van Krieken

Antonio Vergari

Andrea Passerini

...

2024/2/19

A-nesi: A scalable approximate method for probabilistic neurosymbolic inference

Advances in Neural Information Processing Systems

Emile van Krieken

Thiviyan Thanapalasingam

Jakub Tomczak

Frank Van Harmelen

Annette Ten Teije

2024/2/13

Optimisation in Neurosymbolic Learning Systems

Emile van Krieken

2024/1/15

GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks

arXiv preprint arXiv:2310.03399

Taraneh Younesian

Thiviyan Thanapalasingam

Emile van Krieken

Daniel Daza

Peter Bloem

2023/10/5

Refining neural network predictions using background knowledge

Machine Learning

Alessandro Daniele

Emile van Krieken

Luciano Serafini

Frank van Harmelen

2023/9

IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation

arXiv preprint arXiv:2307.06698

Thiviyan Thanapalasingam

Emile van Krieken

Peter Bloem

Paul Groth

2023/7/13

Analyzing differentiable fuzzy logic operators

Artificial Intelligence

Emile van Krieken

Erman Acar

Frank van Harmelen

2020/2/14

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

Kim Van Den Houten

Emile Van Krieken

Bernd Heidergott

2022/12/11

Prompting as probing: Using language models for knowledge base construction

arXiv preprint arXiv:2208.11057

Dimitrios Alivanistos

Selene Báez Santamaría

Michael Cochez

Jan-Christoph Kalo

Emile van Krieken

...

2022/8/23

Storchastic: A framework for general stochastic automatic differentiation

Advances in Neural Information Processing Systems

Emile van Krieken

Jakub Tomczak

Annette Ten Teije

2021/12/6

Analyzing Differentiable Fuzzy Implications

Emile van Krieken

Erman Acar

Frank van Harmelen

2020/9/12

See List of Professors in Emile van Krieken University(Vrije Universiteit Amsterdam)

Co-Authors

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