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12/16/2022
Robust Explanation Constraints for Neural Networks
Post-hoc explanation methods are used with the intent of providing insig...
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12/05/2022
Explaining Link Predictions in Knowledge Graph Embedding Models with Influential Examples
We study the problem of explaining link predictions in the Knowledge Gra...
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11/17/2022
Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients
Background: Stratifying cancer patients according to risk of relapse can...
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11/11/2021
Poisoning Knowledge Graph Embeddings via Relation Inference Patterns
We study the problem of generating data poisoning attacks against Knowle...
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11/04/2021
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods
Despite the widespread use of Knowledge Graph Embeddings (KGE), little i...
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05/18/2021
Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes
Numeric values associated to edges of a knowledge graph have been used t...
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03/16/2021
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
Counterfactual explanations (CEs) are a practical tool for demonstrating...
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06/25/2020
Background Knowledge Injection for Interpretable Sequence Classification
Sequence classification is the supervised learning task of building mode...
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04/30/2020
Knowledge Graph Embeddings and Explainable AI
Knowledge graph embeddings are now a widely adopted approach to knowledg...
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12/20/2019
Probability Calibration for Knowledge Graph Embedding Models
Knowledge graph embedding research has overlooked the problem of probabi...
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11/13/2018