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06/17/2023
Understanding Certified Training with Interval Bound Propagation
As robustness verification methods are becoming more precise, training c...
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05/08/2023
TAPS: Connecting Certified and Adversarial Training
Training certifiably robust neural networks remains a notoriously hard p...
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03/09/2023
Efficient Certified Training and Robustness Verification of Neural ODEs
Neural Ordinary Differential Equations (NODEs) are a novel neural archit...
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01/14/2023
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)
This paper presents a summary and meta-analysis of the first three itera...
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12/20/2022
The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results
This report summarizes the 3rd International Verification of Neural Netw...
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10/10/2022
Certified Training: Small Boxes are All You Need
We propose the novel certified training method, SABR, which outperforms ...
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05/27/2022
(De-)Randomized Smoothing for Decision Stump Ensembles
Tree-based models are used in many high-stakes application domains such ...
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04/30/2022
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
State-of-the-art neural network verifiers are fundamentally based on one...
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04/01/2022
Robust and Accurate – Compositional Architectures for Randomized Smoothing
Randomized Smoothing (RS) is considered the state-of-the-art approach to...
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10/14/2021
Effective Certification of Monotone Deep Equilibrium Models
Monotone Operator Equilibrium Models (monDEQs) represent a class of mode...
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06/13/2021
Boosting Randomized Smoothing with Variance Reduced Classifiers
Randomized Smoothing (RS) is a promising method for obtaining robustness...
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03/05/2021
