Project: safeai.ethz.ch

Safe Artificial Intelligence
Building safe and robust artifical intelligence systems.

Startups

The world's first platform for building and deploying Trustworthy AI.

Publications

2022

Shared Certificates for Neural Network Verification
Marc Fischer*, Christian Sprecher*, Dimitar I. Dimitrov, Gagandeep Singh, Martin Vechev
CAV 2022 * Equal contribution
Robust and Accurate - Compositional Architectures for Randomized Smoothing
Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
SRML@ICLR 2022
Boosting Randomized Smoothing with Variance Reduced Classifiers
Miklós Z. Horváth, Mark Niklas Müller, Marc Fischer, Martin Vechev
ICLR (Spotlight) 2022
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
Claudio Ferrari, Mark Niklas Müller, Nikola Jovanović, Martin Vechev
ICLR 2022
Provably Robust Adversarial Examples
Dimitar I. Dimitrov, Gagandeep Singh, Timon Gehr, Martin Vechev
ICLR 2022
Fair Normalizing Flows
Mislav Balunović, Anian Ruoss, Martin Vechev
ICLR 2022
Bayesian Framework for Gradient Leakage
Mislav Balunović, Dimitar I. Dimitrov, Robin Staab, Martin Vechev
ICLR 2022
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations
Mark Niklas Müller, Gleb Makarchuk, Gagandeep Singh, Markus Püschel, Martin Vechev
POPL 2022

2021

Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev
NeurIPS 2021
The Fundamental Limits of Interval Arithmetic for Neural Networks
Matthew Mirman, Maximilian Baader, Martin Vechev
arXiv 2021
Effective Certification of Monotone Deep Equilibrium Models
Mark Niklas Müller, Robin Staab, Marc Fischer, Martin Vechev
arXiv 2021
Robustness Certification for Point Cloud Models
Tobias Lorenz, Anian Ruoss, Mislav Balunović, Gagandeep Singh, Martin Vechev
ICCV 2021
Scalable Polyhedral Verification of Recurrent Neural Networks
Wonryong Ryou, Jiayu Chen, Mislav Balunović, Gagandeep Singh, Andrei Dan, Martin Vechev
CAV 2021
Scalable Certified Segmentation via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
ICML 2021
Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao, Pavol Bielik, Petar Tsankov, Martin Vechev
AutoML@ICML (Oral) 2021
Certified Defenses: Why Tighter Relaxations May Hurt Training
Nikola Jovanović*, Mislav Balunović*, Maximilian Baader, Martin Vechev
arXiv 2021 * Equal contribution
Fast and Precise Certification of Transformers
Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin Vechev
PLDI 2021
Certify or Predict: Boosting Certified Robustness with Compositional Architectures
Mark Niklas Müller, Mislav Balunović, Martin Vechev
ICLR 2021
Scaling Polyhedral Neural Network Verification on GPUs
Christoph Müller*, François Serre*, Gagandeep Singh, Markus Püschel, Martin Vechev
MLSys 2021 * Equal contribution
Robustness Certification with Generative Models
Matthew Mirman, Alexander Hägele, Timon Gehr, Pavol Bielik, Martin Vechev
PLDI 2021
Efficient Certification of Spatial Robustness
Anian Ruoss, Maximilian Baader, Mislav Balunović, Martin Vechev
AAAI 2021

2020

Learning Certified Individually Fair Representations
Anian Ruoss, Mislav Balunović, Marc Fischer, Martin Vechev
NeurIPS 2020
Certified Defense to Image Transformations via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
NeurIPS 2020
Adversarial Attacks on Probabilistic Autoregressive Forecasting Models
Raphaël Dang-Nhu, Gagandeep Singh, Pavol Bielik, Martin Vechev
ICML 2020
Adversarial Training and Provable Defenses: Bridging the Gap
Mislav Balunović, Martin Vechev
ICLR (Oral) 2020
Universal Approximation with Certified Networks
Maximilian Baader, Matthew Mirman, Martin Vechev
ICLR 2020
Robustness Certification of Generative Models
Mathew Mirman, Timon Gehr, Martin Vechev
arXiv 2020

2019

Beyond the Single Neuron Convex Barrier for Neural Network Certification
Gagandeep Singh, Rupanshu Ganvir, Markus Püschel, Martin Vechev
NeurIPS 2019
Certifying Geometric Robustness of Neural Networks
Mislav Balunović, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin Vechev
NeurIPS 2019
Online Robustness Training for Deep Reinforcement Learning
Marc Fischer, Matthew Mirman, Steven Stalder, Martin Vechev
arXiv 2019
DL2: Training and Querying Neural Networks with Logic
Marc Fischer, Mislav Balunović, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin Vechev
ICML 2019
Boosting Robustness Certification of Neural Networks
Gagandeep Singh, Timon Gehr, Markus Püschel, Martin Vechev
ICLR 2019
A Provable Defense for Deep Residual Networks
Matthew Mirman, Gagandeep Singh, Martin Vechev
ArXiv 2019
An Abstract Domain for Certifying Neural Networks
Gagandeep Singh, Timon Gehr, Markus Püschel, Martin Vechev
ACM POPL 2019

2018

Fast and Effective Robustness Certification
Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, Martin Vechev
NIPS 2018
AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation
Timon Gehr, Matthew Mirman, Dana Drachsler-Cohen, Petar Tsankov, Swarat Chaudhuri, Martin Vechev
IEEE S&P 2018

Talks

Safe and Robust Deep Learning
Waterloo ML + Security + Verification Workshop
Safe and Robust Deep Learning
University of Edinburgh, Robust Artificial Intelligence for Neurorobotics 2019
AI2: AI Safety and Robustness with Abstract Interpretation
Machine Learning meets Formal Methods, FLOC 2018