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Stephan Rabanser
Stephan Rabanser
University of Toronto & Vector Institute for Artificial Intelligence
Dirección de correo verificada de cs.toronto.edu - Página principal
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Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
S Rabanser, S Günnemann, Z Lipton
Advances in Neural Information Processing Systems (NeurIPS), 2019
3282019
Introduction to Tensor Decompositions and their Applications in Machine Learning
S Rabanser, O Shchur, S Günnemann
arXiv preprint arXiv:1711.10781, 2017
2632017
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models
S Rabanser, T Januschowski, V Flunkert, D Salinas, J Gasthaus
KDD Workshop on Mining and Learning from Time Series (MiLeTS) 2020, 2020
242020
Selective Prediction via Training Dynamics
S Rabanser, A Thudi, K Hamidieh, A Dziedzic, I Bahceci, AB Sediq, ...
14*2023
Training Private Models That Know What They Don't Know
S Rabanser, A Thudi, A Thakurta, K Dvijotham, N Papernot
Advances in Neural Information Processing Systems (NeurIPS), 2023
32023
Intrinsic Anomaly Detection for Multi-Variate Time Series
S Rabanser*, T Januschowski*, K Rasul, O Borchert, R Kurle, J Gasthaus, ...
arXiv preprint arXiv:2206.14342, 2022
32022
p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations
A Dziedzic*, S Rabanser*, M Yaghini*, A Ale, MA Erdogdu, N Papernot
arXiv preprint arXiv:2207.12545, 2022
22022
Robust and Actively Secure Serverless Collaborative Learning
O Franzese*, A Dziedzic*, CA Choquette-Choo, MR Thomas, MA Kaleem, ...
Advances in Neural Information Processing Systems (NeurIPS), 2023
2023
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