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Publications

 

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Displaying results 31 to 40 of 515.
  1. Nicolò Parmiggiani; Andrea Bulgarelli; Alessandro Ursi; Antonio Macaluso; Ambra Di Piano; Valentina Fioretti; Alessio Aboudan; Leonardo Baroncelli; Antonio Addis; Marco Tavani; Carlotta Pittori

    A Deep-learning Anomaly-detection Method to Identify Gamma-Ray Bursts in the Ratemeters of the AGILE Anticoincidence System

    In: The Astrophysical Journal (ApJ), Vol. 945, No. 2, Pages 1-12, IOP, 3/2023.

  2. DeepLSF: Fusing Knowledge and Data for Time Series Forecasting

    In: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. NA, Page NA, IEEE, 2023.

  3. Ho Minh Duy Nguyen; Hoang Nguyen; Nghiem T. Diep; Tan Pham; Tri Cao; Binh T. Nguyen; Paul Swoboda; Nhat Ho; Shadi Albarqouni; Pengtao Xie; Daniel Sonntag; Mathias Niepert

    LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

    In: The Thirty-Seventh Annual Conference on Neural Information Processing Systems (NeurIPS 2023). Neural Information Processing Systems (NeurIPS), …

  4. Deep Learning Architectures For the Prediction of YY1-Mediated Chromatin Loops

    In: Xuan Guo; Serghei Mangul; Murray Patterson; Alexander Zelikovsky (Hrsg.). Bioinformatics Research and Applications, 19th International Symposium, …

  5. Faiza Mehmood; Rehab Shahzadi; Hina Ghafoor; Muhammad Nabeel Asim; Muhammad Usman Ghani; Waqar Mahmood; Andreas Dengel

    EnML: Multi-label Ensemble Learning for Urdu Text Classification

    In: ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 22, Pages 1-31, ACM, 9/2023.

  6. Translating theory into practice: assessing the privacy implications of concept-based explanations for biomedical AI

    In: Juan Guillermo Diaz Ochoa (Hrsg.). Frontiers in Bioinformatics, Vol. 3, Pages 1-19, Frontiers Media SA, 7/2023.

  7. Latent Inspector: An Interactive Tool for Probing Neural Network Behaviors Through Arbitrary Latent Activation

    In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. International Joint Conference on Artificial …

  8. Alejandro Molina; Antonio Vergari; Karl Stelzner; Robert Peharz; Pranav Subramani; Nicola Di Mauro; Pascal Poupart; Kristian Kersting

    SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks

    In: Computing Research Repository eprint Journal (CoRR), Vol. abs/1901.03704, Pages 0-10, arXiv, 2019.

  9. Robert Peharz; Antonio Vergari; Karl Stelzner; Alejandro Molina; Martin Trapp; Xiaoting Shao; Kristian Kersting; Zoubin Ghahramani

    Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

    In: Amir Globerson; Ricardo Silva (Hrsg.). Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence. Conference in …