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ORCIDMaximilian Baader
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2020 – today
- 2024
[b1]Maximilian Baader:
Expressivity of Certified Neural Networks. ETH Zurich, Zürich, Switzerland, 2024- [c9]Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev:
Expressivity of ReLU-Networks under Convex Relaxations. ICLR 2024 - [i15]Jasper Dekoninck, Mark Niklas Müller, Maximilian Baader, Marc Fischer, Martin T. Vechev:
Evading Data Contamination Detection for Language Models is (too) Easy. CoRR abs/2402.02823 (2024) - [i14]Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev:
SPEAR: Exact Gradient Inversion of Batches in Federated Learning. CoRR abs/2403.03945 (2024) - [i13]Stefan Balauca, Mark Niklas Müller, Yuhao Mao, Maximilian Baader, Marc Fischer, Martin T. Vechev:
Overcoming the Paradox of Certified Training with Gaussian Smoothing. CoRR abs/2403.07095 (2024) - [i12]Ivo Petrov, Dimitar I. Dimitrov, Maximilian Baader, Mark Niklas Müller, Martin T. Vechev:
DAGER: Exact Gradient Inversion for Large Language Models. CoRR abs/2405.15586 (2024) - [i11]Philip Sosnin, Mark Niklas Müller, Maximilian Baader, Calvin Tsay, Matthew Wicker:
Certified Robustness to Data Poisoning in Gradient-Based Training. CoRR abs/2406.05670 (2024) - [i10]Jasper Dekoninck, Maximilian Baader, Martin T. Vechev:
Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation. CoRR abs/2409.00696 (2024) - 2023
- [j3]Benjamin Bichsel, Anouk Paradis, Maximilian Baader, Martin T. Vechev:
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. Quantum 7: 1185 (2023) - [i9]Benjamin Bichsel, Maximilian Baader, Anouk Paradis, Martin T. Vechev:
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation. CoRR abs/2304.00921 (2023) - [i8]Maximilian Baader, Mark Niklas Müller, Yuhao Mao, Martin T. Vechev:
Expressivity of ReLU-Networks under Convex Relaxations. CoRR abs/2311.04015 (2023) - 2022
- [j2]Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
On the Paradox of Certified Training. Trans. Mach. Learn. Res. 2022 (2022) - [j1]Matthew Mirman, Maximilian Baader, Martin T. Vechev:
The Fundamental Limits of Neural Networks for Interval Certified Robustness. Trans. Mach. Learn. Res. 2022 (2022) - [c8]Momchil Peychev
, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
Latent Space Smoothing for Individually Fair Representations. ECCV (13) 2022: 535-554 - 2021
- [c7]Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev:
Efficient Certification of Spatial Robustness. AAAI 2021: 2504-2513 - [c6]Marc Fischer, Maximilian Baader, Martin T. Vechev:
Scalable Certified Segmentation via Randomized Smoothing. ICML 2021: 3340-3351 - [c5]Gregory Bonaert, Dimitar I. Dimitrov, Maximilian Baader, Martin T. Vechev:
Fast and precise certification of transformers. PLDI 2021: 466-481 - [i7]Nikola Jovanovic, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
Certified Defenses: Why Tighter Relaxations May Hurt Training? CoRR abs/2102.06700 (2021) - [i6]Marc Fischer, Maximilian Baader, Martin T. Vechev:
Scalable Certified Segmentation via Randomized Smoothing. CoRR abs/2107.00228 (2021) - [i5]Momchil Peychev, Anian Ruoss, Mislav Balunovic, Maximilian Baader, Martin T. Vechev:
Latent Space Smoothing for Individually Fair Representations. CoRR abs/2111.13650 (2021) - [i4]Matthew Mirman, Maximilian Baader, Martin T. Vechev:
The Fundamental Limits of Interval Arithmetic for Neural Networks. CoRR abs/2112.05235 (2021) - 2020
- [c4]Maximilian Baader, Matthew Mirman, Martin T. Vechev:
Universal Approximation with Certified Networks. ICLR 2020 - [c3]Marc Fischer, Maximilian Baader, Martin T. Vechev:
Certified Defense to Image Transformations via Randomized Smoothing. NeurIPS 2020 - [c2]Benjamin Bichsel, Maximilian Baader, Timon Gehr, Martin T. Vechev:
Silq: a high-level quantum language with safe uncomputation and intuitive semantics. PLDI 2020: 286-300 - [i3]Marc Fischer, Maximilian Baader, Martin T. Vechev:
Certification of Semantic Perturbations via Randomized Smoothing. CoRR abs/2002.12463 (2020) - [i2]Anian Ruoss, Maximilian Baader, Mislav Balunovic, Martin T. Vechev:
Efficient Certification of Spatial Robustness. CoRR abs/2009.09318 (2020)
2010 – 2019
- 2019
- [c1]Mislav Balunovic, Maximilian Baader, Gagandeep Singh, Timon Gehr, Martin T. Vechev:
Certifying Geometric Robustness of Neural Networks. NeurIPS 2019: 15287-15297 - [i1]Maximilian Baader, Matthew Mirman, Martin T. Vechev:
Universal Approximation with Certified Networks. CoRR abs/1909.13846 (2019)
Coauthor Index
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