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
   

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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
   

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3. 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
   

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4. Selective Classification Via Neural Network Training Dynamics

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

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5. 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
   

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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

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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
   

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8. Denoising Spectral Clustering Through Latent Data Decomposition

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

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9. Improving Online GMM Learning Via Covariance Weighting

   
   Stephan Rabanser*, Maksim Greiner
   (2018) Preprint
   

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

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

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* indicates joint first-authorship.