Publications

  1. Training Private Models That Know What They Don’t Know


    Stephan Rabanser*, Anvith Thudi, Abhradeep Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot
    Advances in Neural Information Processing Systems (2023) Conference

    Paper Slides

  2. Robust and Actively Secure Serverless Collaborative Learning


    Olive Franzese*, Adam Dziedzic*, Christopher A Choquette-Choo, Mark R Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang
    Advances in Neural Information Processing Systems (2023) Conference

    Paper

  3. Selective Classification Via Neural Network Training Dynamics


    Stephan Rabanser*, Anvith Thudi, Kimia Hamidieh, Adam Dziedzic, Nicolas Papernot
    arXiv preprint arXiv:2205.13532 (2022) Preprint

    Paper Slides

  4. Intrinsic Anomaly Detection for Multi-Variate Time Series


    Stephan Rabanser*, Tim Januschowski*, Kashif Rasul, Oliver Borchert, Richard Kurle, Jan Gasthaus, Michael Bohlke-Schneider, Nicolas Papernot, Valentin Flunkert
    arXiv preprint arXiv:2206.14342 (2022) Preprint

    Paper

  5. p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations


    Adam Dziedzic*, Stephan Rabanser*, Mohammad Yaghini*, Armin Ale, Murat A. Erdogdu, Nicolas Papernot
    arXiv preprint arXiv:2207.12545 (2022) Preprint

    Paper

  6. The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models


    Stephan Rabanser*, Tim Januschowski, Valentin Flunkert, David Salinas, Jan Gasthaus
    In 7th KDD Workshop on Mining and Learning from Time Series (MiLeTS) (2020) Workshop Oral

    Paper Slides Video

  7. Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift


    Stephan Rabanser*, Stephan Günnemann, Zachary Lipton
    In Advances in Neural Information Processing Systems (2019) Conference

    Paper Poster Slides Code

  8. Improving Online GMM Learning Via Covariance Weighting


    Stephan Rabanser*, Maksim Greiner
    (2018) Preprint

    Paper

  9. Denoising Spectral Clustering Through Latent Data Decomposition


    Stephan Rabanser*, Oleksandr Shchur, Stephan Günnemann
    (2018) Preprint

    Paper

  10. Introduction to Tensor Decompositions and their Applications in Machine Learning


    Stephan Rabanser*, Oleksandr Shchur, Stephan Günnemann
    arXiv preprint arXiv:1711.10781 (2017) Preprint

    Paper

* indicates joint first-authorship.