Publications

Journal Articles

2021

  1. Alexe L. Haywood, Joseph Redshaw, Magnus W.D. Hanson-Heine, Adam Taylor, Alex Brown, Andrew M. Mason, Thomas Gärtner, and Jonathan D. Hirst. 2021. Kernel methods for predicting yields of chemical reactions. Journal of Chemical Information and Modeling.

Top Conference Articles

2022

  1. Maximilian Thiessen and Thomas Gärtner. 2022. Online learning of convex sets on graphs. In ECMLPKDD.
  2. Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice, and Maximilian Thiessen. 2022. Active Learning of Classifiers with Label and Seed Queries. In NeurIPS.

2021

  1. Maximilian Thiessen and Thomas Gärtner. 2021. Active Learning of Convex Halfspaces on Graphs. In NeurIPS.

Other Articles

2022

  1. Markus Schedl, Stefan Brandl, Oleg Lesota, Emilia Parada-Cabaleiro, David Penz, and Navid Rekabsaz. 2022. LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. In CHIIR. Association for Computing Machinery. [doi] [url]
  2. Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, and Markus Schedl. 2022. EmoMTB: Emotion-Aware Music Tower Blocks. In ICMR. Association for Computing Machinery. [doi] [url]
  3. Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner. 2022. Weisfeiler and Leman Return with Graph Transformations. In MLG workshop at ECMLPKDD.
  4. Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner. 2022. Reducing Learning on Cell Complexes to Graphs. In GTRL workshop at ICLR.
  5. Christian Ganhör, David Penz, Navid Rekabsaz, Oleg Lesota, and Markus Schedl. 2022. Unlearning Protected User Attributes in Recommendations with Adversarial Training. In SIGIR. Association for Computing Machinery. [doi] [url]

2021

  1. Maximilian Thiessen and Thomas Gärtner. 2021. Active Learning Convex Halfspaces on Graphs. In SubSetML workshop at ICML.
  2. Fares Meghdouri, Thomas Schmied, Thomas Gärtner, and Tanja Zseby. 2021. Controllable Network Data Balancing With GANs. In NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications. [url]
  3. Alexander Krauck, David Penz, and Markus Schedl. 2021. Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features. In RecSys. Association for Computing Machinery. [doi] [url]

2020

  1. Maximilian Thiessen and Thomas Gärtner. 2020. Active Learning on Graphs with Geodesically Convex Classes. In MLG workshop at KDD.
  2. Thomas Schmied and Maximilian Thiessen. 2020. Efficient Reinforcement Learning via Self-supervised learning and Model-based methods. In RWRL workshop at NeurIPS.