Maximilian Baader

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 26

Top Topics

Gaussian Smoothing

Fundamental Limits

Interval Arithmetic

Top Venues

Trans. Mach. Learn. Res.

Publications

Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
DAGER: Exact Gradient Inversion for Large Language Models. CoRR (2024)
Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker
Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR (2024)
Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin T. Vechev
Evading Data Contamination Detection for Language Models is (too) Easy. CoRR (2024)
Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
Expressivity of ReLU-Networks under Convex Relaxations. ICLR (2024)
Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev
SPEAR: Exact Gradient Inversion of Batches in Federated Learning. CoRR (2024)
Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin T. Vechev
Overcoming the Paradox of Certified Training with Gaussian Smoothing. CoRR (2024)
Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin T. Vechev
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. Quantum 7 (2023)
Benjamin Bichsel, Maximilian Baader, Anouk Paradis, Martin T. Vechev
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. CoRR (2023)
Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev
Expressivity of ReLU-Networks under Convex Relaxations. CoRR (2023)
Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
On the Paradox of Certified Training. Trans. Mach. Learn. Res. 2022 (2022)
Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
Latent Space Smoothing for Individually Fair Representations. ECCV (13) (2022)
Matthew Mirman, Maximilian Baader, Martin T. Vechev
The Fundamental Limits of Neural Networks for Interval Certified Robustness. Trans. Mach. Learn. Res. 2022 (2022)
Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev
Fast and precise certification of transformers. PLDI (2021)
Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
Efficient Certification of Spatial Robustness. AAAI (2021)
Marc Fischer, Maximilian Baader, Martin T. Vechev
Scalable Certified Segmentation via Randomized Smoothing. CoRR (2021)
Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
Certified Defenses: Why Tighter Relaxations May Hurt Training? CoRR (2021)
Matthew Mirman, Maximilian Baader, Martin T. Vechev
The Fundamental Limits of Interval Arithmetic for Neural Networks. CoRR (2021)
Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev
Latent Space Smoothing for Individually Fair Representations. CoRR (2021)
Marc Fischer, Maximilian Baader, Martin T. Vechev
Scalable Certified Segmentation via Randomized Smoothing. ICML (2021)
Maximilian Baader, Matthew Mirman, Martin T. Vechev
Universal Approximation with Certified Networks. ICLR (2020)
Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin T. Vechev
Silq: a high-level quantum language with safe uncomputation and intuitive semantics. PLDI (2020)
Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev
Efficient Certification of Spatial Robustness. CoRR (2020)
Marc Fischer, Maximilian Baader, Martin T. Vechev
Certified Defense to Image Transformations via Randomized Smoothing. NeurIPS (2020)
Marc Fischer, Maximilian Baader, Martin T. Vechev
Certification of Semantic Perturbations via Randomized Smoothing. CoRR (2020)
Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev
Certifying Geometric Robustness of Neural Networks. NeurIPS (2019)
Maximilian Baader, Matthew Mirman, Martin T. Vechev
Universal Approximation with Certified Networks. CoRR (2019)