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09/01/2023
On the Aggregation of Rules for Knowledge Graph Completion
Rule learning approaches for knowledge graph completion are efficient, i...
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07/26/2023
Learning Disentangled Discrete Representations
Recent successes in image generation, model-based reinforcement learning...
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06/27/2023
Planning Landmark Based Goal Recognition Revisited: Does Using Initial State Landmarks Make Sense?
Goal recognition is an important problem in many application domains (e....
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05/05/2023
Learning Decision Trees with Gradient Descent
Decision Trees (DTs) are commonly used for many machine learning tasks d...
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01/25/2023
Leveraging Planning Landmarks for Hybrid Online Goal Recognition
Goal recognition is an important problem in many application domains (e....
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01/13/2023
Investigating the Combination of Planning-Based and Data-Driven Methods for Goal Recognition
An important feature of pervasive, intelligent assistance systems is the...
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07/18/2022
Outlier Explanation via Sum-Product Networks
Outlier explanation is the task of identifying a set of features that di...
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06/10/2022
Explaining Neural Networks without Access to Training Data
We consider generating explanations for neural networks in cases where t...
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01/19/2022
Top-Down Influence? Predicting CEO Personality and Risk Impact from Speech Transcripts
How much does a CEO's personality impact the performance of their compan...
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10/11/2021
Exchangeability-Aware Sum-Product Networks
Sum-Product Networks (SPNs) are expressive probabilistic models that pro...
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12/10/2020
xRAI: Explainable Representations through AI
We present xRAI an approach for extracting symbolic representations of t...
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10/19/2020
Neural Architecture Performance Prediction Using Graph Neural Networks
In computer vision research, the process of automating architecture engi...
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10/09/2020
Smooth Variational Graph Embeddings for Efficient Neural Architecture Search
In this paper, we propose an approach to neural architecture search (NAS...
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04/09/2020
Reinforced Anytime Bottom Up Rule Learning for Knowledge Graph Completion
Most of todays work on knowledge graph completion is concerned with sub-...
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12/11/2019
A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction
In computer vision research, the process of automating architecture engi...
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04/12/2019
Political Text Scaling Meets Computational Semantics
During the last fifteen years, text scaling approaches have become a cen...
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11/18/2015
Using Abduction in Markov Logic Networks for Root Cause Analysis
IT infrastructure is a crucial part in most of today's business operatio...
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04/16/2013
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models
RockIt is a maximum a-posteriori (MAP) query engine for statistical rela...
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08/15/2012