Rabanser, Stephan

8 publications

ICML 2025 Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese, Xiao Wang, Adrian Weller, Nicolas Papernot

NeurIPS 2025 Gatekeeper: Improving Model Cascades Through Confidence Tuning Stephan Rabanser, Nathalie Rauschmayr, Achin Kulshrestha, Petra Poklukar, Wittawat Jitkrittum, Sean Augenstein, Congchao Wang, Federico Tombari

TMLR 2025 Selective Prediction via Training Dynamics Stephan Rabanser, Anvith Thudi, Kimia Hamidieh, Adam Dziedzic, Israfil Bahceci, Akram Bin Sediq, Hamza Sokun, Nicolas Papernot

ICML 2025 Suitability Filter: A Statistical Framework for Classifier Evaluation in Real-World Deployment Settings Angéline Pouget, Mohammad Yaghini, Stephan Rabanser, Nicolas Papernot

NeurIPS 2025 What Does It Take to Build a Performant Selective Classifier? Stephan Rabanser, Nicolas Papernot

NeurIPS 2023 Robust and Actively Secure Serverless Collaborative Learning Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang

NeurIPS 2023 Training Private Models That Know What They Don’t Know Stephan Rabanser, Anvith Thudi, Abhradeep Guha Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot

NeurIPS 2019 Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser, Stephan Günnemann, Zachary Lipton