List of the involved PhD Students
Rodrigo Castellano OntiverosUniversità degli Studi di Siena
Multiple Representation Models in the context of Neural Symbolic Methods.
Neuro-Symboic AI · Explainable AI · Logic
Marco GrilloPoznan University of Technology
Theoretical Foundations of Learning from Multiple Representations.
Theoretical approach · Data analysis · New algorithms
Fabian HoppeVrije Universiteit Amsterdam
Combining Large Language Models and Knowledge Graphs.
Neuro-symbolic AI · Large Language Models · Knowledge Graphs
Ying JiaoKU Leuven
LMR via Neural Probabilistic Logic programming.
Neuro-symbolic · Approximate Inference · Neuro-symbolic Generative Models
Louis Mozart Kamdem TeyouUniversität Paderborn
Class Expression Learning with Multiple Representations.
Explainable AI · Knowledge Graphs · Function Spaces
Pim KerkhovenUmea University
Socio-ethical Requirements of Learning with Multiple Representations.
Responsible AI · Requirement Analysis · Machine Learning
Tobias OberkoflerLudwig Maximillians University
Learning with Multiple Representations of Data
Algorithms · Formal Guarantees · Weak Supervision
Isaac Jerome RobertsBielefeld University
Multiple Representation Learning in Visualization.
Explainable AI · Dimensionality Reduction · Embedding Spaces
Charalampos ShimillasUniversity of Cyprus
LMR for Fault Isolation in Critical Infrastructure Systems.
Deep Learning · Online learning · Time series · Critical Infrastructures (CIs) · Fault isolation
Effrosyni SokliUniversità degli Studi di Milano-Bicocca
Learning with Multiple Representations in Search and Recommendation.
Information Retrieval · Knowledge Representation · Natural Language Processing (NLP)
Rodrigo Castellano OntiverosUniversità degli Studi di Siena
Multiple Representation Models in the context of Neural Symbolic Methods.
Multiple Representation Models in the context of Neural Symbolic Methods.
Neuro-Symboic AI · Explainable AI · Logic
Marco GrilloPoznan University of Technology
Theoretical Foundations of Learning from Multiple Representations.
Theoretical Foundations of Learning from Multiple Representations.
Theoretical approach · Data analysis · New algorithms
Fabian HoppeVrije Universiteit Amsterdam
Combining Large Language Models and Knowledge Graphs.
Combining Large Language Models and Knowledge Graphs.
Neuro-symbolic AI · Large Language Models · Knowledge Graphs
Ying JiaoKU Leuven
LMR via Neural Probabilistic Logic programming.
LMR via Neural Probabilistic Logic programming.
Neuro-symbolic · Approximate Inference · Neuro-symbolic Generative Models
Louis Mozart Kamdem TeyouUniversität Paderborn
Class Expression Learning with Multiple Representations.
Class Expression Learning with Multiple Representations.
Explainable AI · Knowledge Graphs · Function Spaces
Pim KerkhovenUmea University
Socio-ethical Requirements of Learning with Multiple Representations.
Socio-ethical Requirements of Learning with Multiple Representations.
Responsible AI · Requirement Analysis · Machine Learning
Tobias OberkoflerLudwig Maximillians University
Learning with Multiple Representations of Data
Learning with Multiple Representations of Data
Algorithms · Formal Guarantees · Weak Supervision
Isaac Jerome RobertsBielefeld University
Multiple Representation Learning in Visualization.
Multiple Representation Learning in Visualization.
Explainable AI · Dimensionality Reduction · Embedding Spaces
Charalampos ShimillasUniversity of Cyprus
LMR for Fault Isolation in Critical Infrastructure Systems.
LMR for Fault Isolation in Critical Infrastructure Systems.
Deep Learning · Online learning · Time series · Critical Infrastructures (CIs) · Fault isolation
Effrosyni SokliUniversità degli Studi di Milano-Bicocca
Learning with Multiple Representations in Search and Recommendation.
Learning with Multiple Representations in Search and Recommendation.
Information Retrieval · Knowledge Representation · Natural Language Processing (NLP)
