Publications
2024
Ward: Provable RAG Dataset Inference via LLM Watermarks
Nikola Jovanović, Robin Staab, Maximilian Baader, Martin Vechev
arXiv
2024
A Unified Approach to Routing and Cascading for LLMs
Jasper Dekoninck, Maximilian Baader, Martin Vechev
ArXiv
2024
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation
Jasper Dekoninck, Maximilian Baader, Martin Vechev
ArXiv
2024
DAGER: Exact Gradient Inversion for Large Language Models
Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev
ArXiv
2024
Expressivity of ReLU-Networks under Convex Relaxations
Maximilian Baader*, Mark Niklas Müller*, Yuhao Mao, Martin Vechev
ICLR
2024
* Equal contribution
SPEAR: Exact Gradient Inversion of Batches in Federated Learning
Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin Vechev
ArXiv
2024
Overcoming the Paradox of Certified Training with Gaussian Smoothing
Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin Vechev
arXiv
2024
Evading Data Contamination Detection for Language Models is (too) Easy
Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin Vechev
arXiv
2024
2023
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation
Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin Vechev
Quantum Journal
2023
2022
Latent Space Smoothing for Individually Fair Representations
Momchil Peychev, Anian Ruoss, Mislav Balunović, Maximilian Baader, Martin Vechev
ECCV
2022
On the Paradox of Certified Training
Nikola Jovanović*, Mislav Balunović*, Maximilian Baader, Martin Vechev
TMLR
2022
* Equal contribution
The Fundamental Limits of Neural Networks for Interval Certified Robustness
Matthew Mirman, Maximilian Baader, Martin Vechev
TMLR
2022
2021
Scalable Certified Segmentation via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
ICML
2021
Fast and Precise Certification of Transformers
Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin Vechev
PLDI
2021
Efficient Certification of Spatial Robustness
Anian Ruoss, Maximilian Baader, Mislav Balunović, Martin Vechev
AAAI
2021
2020
Certified Defense to Image Transformations via Randomized Smoothing
Marc Fischer, Maximilian Baader, Martin Vechev
NeurIPS
2020
Silq: A High-Level Quantum Language with Safe Uncomputation and Intuitive Semantics
Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin Vechev
PLDI
2020
Universal Approximation with Certified Networks
Maximilian Baader, Matthew Mirman, Martin Vechev
ICLR
2020
2019
Certifying Geometric Robustness of Neural Networks
Mislav Balunović, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin Vechev
NeurIPS
2019
Education
- ETH Zurich, 2018 - PhD Candidate in Computer Science
- ETH Zurich , 2016 - 2018 Masters in Physics
- ETH Zurich, 2012 - 2016 Bachelors in Physics
Teaching
- Linear Algebra 2 Spring 2018
- Complex Analysis Autumn 2017
- Linear Algebra 2 Spring 2017
- Complex Analysis Autumn 2016
- Linear Algebra 2 Spring 2016
- Complex Analysis Autumn 2015