Mark Niklas Müller

Orcid: 0000-0002-2496-6542

According to our database¹, Mark Niklas Müller authored at least 31 papers between 2021 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

Training and Certification of Neural Networks with Guarantees.

[BibT_eX]

[DOI]

Mark Niklas Müller

PhD thesis, 2024

Diagnosing Robotics Systems Issues with Large Language Models.

[BibT_eX]

[DOI]

Jordis Emilia Herrmann

Aswath Mandakath Gopinath

Mikael Norrlof

Mark Niklas Müller

CoRR, 2024

Average Certified Radius is a Poor Metric for Randomized Smoothing.

[BibT_eX]

[DOI]

CoRR, 2024

Mitigating Catastrophic Forgetting in Language Transfer via Model Merging.

[BibT_eX]

[DOI]

CoRR, 2024

Code Agents are State of the Art Software Testers.

[BibT_eX]

[DOI]

CoRR, 2024

Certified Robustness to Data Poisoning in Gradient-Based Training.

[BibT_eX]

[DOI]

CoRR, 2024

ConStat: Performance-Based Contamination Detection in Large Language Models.

[BibT_eX]

[DOI]

Jasper Dekoninck

Mark Niklas Müller

Martin T. Vechev

CoRR, 2024

DAGER: Exact Gradient Inversion for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Overcoming the Paradox of Certified Training with Gaussian Smoothing.

[BibT_eX]

[DOI]

CoRR, 2024

SPEAR: Exact Gradient Inversion of Batches in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Evading Data Contamination Detection for Language Models is (too) Easy.

[BibT_eX]

[DOI]

CoRR, 2024

Prompt Sketching for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Understanding Certified Training with Interval Bound Propagation.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Expressivity of ReLU-Networks under Convex Relaxations.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

First three years of the international verification of neural networks competition (VNN-COMP).

[BibT_eX]

[DOI]

Int. J. Softw. Tools Technol. Transf., June, 2023

Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks - Artifact.

[BibT_eX]

[DOI]

Dataset, June, 2023

Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks.

[BibT_eX]

[DOI]

Proc. ACM Program. Lang., 2023

TAPS: Connecting Certified and Adversarial Training.

[BibT_eX]

[DOI]

CoRR, 2023

Automated Classification of Model Errors on ImageNet.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Connecting Certified and Adversarial Training.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Certified Training and Robustness Verification of Neural ODEs.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Certified Training: Small Boxes are All You Need.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

PRIMA: general and precise neural network certification via scalable convex hull approximations.

[BibT_eX]

[DOI]

Proc. ACM Program. Lang., 2022

The Third International Verification of Neural Networks Competition (VNN-COMP 2022): Summary and Results.

[BibT_eX]

[DOI]

CoRR, 2022

Robust and Accurate - Compositional Architectures for Randomized Smoothing.

[BibT_eX]

[DOI]

CoRR, 2022

(De-)Randomized Smoothing for Decision Stump Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Boosting Randomized Smoothing with Variance Reduced Classifiers.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Effective Certification of Monotone Deep Equilibrium Models.

[BibT_eX]

[DOI]

CoRR, 2021

Precise Multi-Neuron Abstractions for Neural Network Certification.

[BibT_eX]

[DOI]

CoRR, 2021

Certify or Predict: Boosting Certified Robustness with Compositional Architectures.

[BibT_eX]

[DOI]

Mark Niklas Müller

Mislav Balunovic

Martin T. Vechev

Proceedings of the 9th International Conference on Learning Representations, 2021

Mark Niklas Müller

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