70 citations
- Arizona State UniversityUS2 papers
- Carnegie Mellon UniversityUS2 papers
- Robert Bosch (Germany)DE2 papers
- Technion – Israel Institute of TechnologyIL2 papers
- University of AmsterdamNL2 papers
- University of BaselCH2 papers
- University of FreiburgDE2 papers
- Department of Physics, Mathematics and InformaticsBY1 paper
- Indian Institute of Technology KanpurIN1 paper
- Karlsruhe Institute of TechnologyDE1 paper
- KU LeuvenBE1 paper
- Lawrence Livermore National LaboratoryUS1 paper
4 papers · 2 filters
Unifying Model Explainability and Robustness via Machine-Checkable Concepts
Vedant Nanda, Till Speicher, John P. Dickerson +2
As deep neural networks (DNNs) get adopted in an ever-increasing number of applications, explainability has emerged as a crucial desideratum for these models. In many real-world ta…
Causal Transfer for Imitation Learning and Decision Making under Sensor-shift
Jalal Etesami, Philipp Geiger
Learning from demonstrations (LfD) is an efficient paradigm to train AI agents. But major issues arise when there are differences between (a) the demonstrator's own sensory input,…
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice
Ruwan Wickramarachchi, Cory Henson, Amit Sheth
The autonomous driving (AD) industry is exploring the use of knowledge graphs (KGs) to manage the vast amount of heterogeneous data generated from vehicular sensors. The various ty…
An Ontology-Aware Framework for Audio Event Classification
Yiwei Sun, Shabnam Ghaffarzadegan
Recent advancements in audio event classification often ignore the structure and relation between the label classes available as prior information. This structure can be defined by…