139 citations · 190 across the 6 of their papers we have counts for
9 papers
Variational Annealing on Graphs for Combinatorial Optimization
Sebastian Sanokowski, Wilhelm Berghammer, Sepp Hochreiter +1
Several recent unsupervised learning methods use probabilistic approaches to solve combinatorial optimization (CO) problems based on the assumption of statistically independent sol…
Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty
Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi +1
Applying a machine learning model for decision-making in the real world requires to distinguish what the model knows from what it does not. A critical factor in assessing the knowl…
Functional trustworthiness of AI systems by statistically valid testing
Bernhard Nessler, Thomas Doms, Sepp Hochreiter
The authors are concerned about the safety, health, and rights of the European citizens due to inadequate measures and procedures required by the current draft of the EU Artificial…
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck +7
We study the problem of choosing algorithm hyper-parameters in unsupervised domain adaptation, i.e., with labeled data in a source domain and unlabeled data in a target domain, dra…
Context-enriched molecule representations improve few-shot drug discovery
Johannes Schimunek, Philipp Seidl, Lukas Friedrich +4
A central task in computational drug discovery is to construct models from known active molecules to find further promising molecules for subsequent screening. However, typically o…
Traffic4cast at NeurIPS 2022 -- Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors
Moritz Neun, Christian Eichenberger, Henry Martin +27
The global trends of urbanization and increased personal mobility force us to rethink the way we live and use urban space. The Traffic4cast competition series tackles this problem…