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ORCIDNicolas M. Müller
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Conference and Workshop Papers
- 2024
[c14]Nicolas M. Müller, Piotr Kawa, Wei Herng Choong, Edresson Casanova, Eren Gölge, Thorsten Müller, Piotr Syga, Philip Sperl, Konstantin Böttinger:
MLAAD: The Multi-Language Audio Anti-Spoofing Dataset. IJCNN 2024: 1-7- [c13]Nicolas M. Müller, Simon Roschmann, Shahbaz Khan, Philip Sperl, Konstantin Böttinger:
Shortcut Detection With Variational Autoencoders. IJCNN 2024: 1-7 - 2023
- [c12]Nicolas M. Müller, Maximilian Burgert, Pascal Debus, Jennifer Williams, Philip Sperl, Konstantin Böttinger:
Protecting Publicly Available Data With Machine Learning Shortcuts. BMVC 2023: 685-698 - [c11]Nicolas M. Müller, Jochen Jacobs, Jennifer Williams, Konstantin Böttinger:
Localized Shortcut Removal. CVPR Workshops 2023: 3721-3725 - [c10]Nicolas M. Müller, Philip Sperl, Konstantin Böttinger:
Complex-valued neural networks for voice anti-spoofing. INTERSPEECH 2023: 3814-3818 - 2022
- [c9]Nicolas M. Müller, Pavel Czempin, Franziska Dieckmann, Adam Froghyar, Konstantin Böttinger:
Does Audio Deepfake Detection Generalize? INTERSPEECH 2022: 2783-2787 - [c8]Nicolas M. Müller, Franziska Dieckmann, Jennifer Williams:
Attacker Attribution of Audio Deepfakes. INTERSPEECH 2022: 2788-2792 - [c7]Nicolas M. Müller, Karla Pizzi, Jennifer Williams:
Human Perception of Audio Deepfakes. DDAM@MM 2022: 85-91 - 2021
- [c6]Nicolas M. Müller, Konstantin Böttinger:
Adversarial Vulnerability of Active Transfer Learning. IDA 2021: 116-127 - [c5]Edresson Casanova, Christopher Shulby, Eren Gölge, Nicolas Michael Müller, Frederico Santos de Oliveira, Arnaldo Candido Jr., Anderson da Silva Soares, Sandra Maria Aluísio, Moacir Antonelli Ponti:
SC-GlowTTS: An Efficient Zero-Shot Multi-Speaker Text-To-Speech Model. Interspeech 2021: 3645-3649 - 2020
- [c4]Nicolas M. Müller, Daniel Kowatsch, Konstantin Böttinger:
Data Poisoning Attacks on Regression Learning and Corresponding Defenses. PRDC 2020: 80-89 - 2019
- [c3]Nicolas M. Müller, Pascal Debus
, Daniel Kowatsch, Konstantin Böttinger:
Distributed Anomaly Detection of Single Mote Attacks in RPL Networks. ICETE (2) 2019: 378-385 - [c2]Nicolas M. Müller, Karla Markert:
Identifying Mislabeled Instances in Classification Datasets. IJCNN 2019: 1-8 - [c1]Nicolas M. Müller, Daniel Kowatsch, Pascal Debus, Donika Mirdita, Konstantin Böttinger:
On GDPR Compliance of Companies' Privacy Policies. TSD 2019: 151-159
Informal and Other Publications
- 2024
- [i20]Nicolas M. Müller, Piotr Kawa, Wei Herng Choong, Edresson Casanova, Eren Gölge, Thorsten Müller, Piotr Syga, Philip Sperl, Konstantin Böttinger:
MLAAD: The Multi-Language Audio Anti-Spoofing Dataset. CoRR abs/2401.09512 (2024) - [i19]Nicolas M. Müller, Piotr Kawa, Shen Hu, Matthias Neu, Jennifer Williams, Philip Sperl, Konstantin Böttinger:
A New Approach to Voice Authenticity. CoRR abs/2402.06304 (2024) - [i18]Daniel Kowatsch, Nicolas M. Müller, Kilian Tscharke, Philip Sperl, Konstantin Böttinger:
Imbalance in Regression Datasets. CoRR abs/2402.11963 (2024) - [i17]Nicolas M. Müller, Nicholas W. D. Evans, Hemlata Tak, Philip Sperl, Konstantin Böttinger:
Harder or Different? Understanding Generalization of Audio Deepfake Detection. CoRR abs/2406.03512 (2024) - [i16]Octavian Pascu, Dan Oneata, Horia Cucu, Nicolas M. Müller:
Easy, Interpretable, Effective: openSMILE for voice deepfake detection. CoRR abs/2408.15775 (2024) - 2023
- [i15]Nicolas M. Müller, Simon Roschmann, Shahbaz Khan, Philip Sperl, Konstantin Böttinger:
Shortcut Detection with Variational Autoencoders. CoRR abs/2302.04246 (2023) - [i14]Nicolas M. Müller, Philip Sperl, Konstantin Böttinger:
Complex-valued neural networks for voice anti-spoofing. CoRR abs/2308.11800 (2023) - [i13]Nicolas M. Müller, Maximilian Burgert, Pascal Debus, Jennifer Williams, Philip Sperl, Konstantin Böttinger:
Protecting Publicly Available Data With Machine Learning Shortcuts. CoRR abs/2310.19381 (2023) - 2022
- [i12]Nicolas M. Müller, Franziska Dieckmann, Jennifer Williams:
Attacker Attribution of Audio Deepfakes. CoRR abs/2203.15563 (2022) - [i11]Nicolas M. Müller, Pavel Czempin, Franziska Dieckmann, Adam Froghyar, Konstantin Böttinger:
Does Audio Deepfake Detection Generalize? CoRR abs/2203.16263 (2022) - [i10]Nicolas M. Müller, Jochen Jacobs, Jennifer Williams, Konstantin Böttinger:
Shortcut Removal for Improved OOD-Generalization. CoRR abs/2211.15510 (2022) - 2021
- [i9]Nicolas M. Müller, Konstantin Böttinger:
Adversarial Vulnerability of Active Transfer Learning. CoRR abs/2101.10792 (2021) - [i8]Pascal Debus, Nicolas M. Müller, Konstantin Böttinger:
Deep Reinforcement Learning for Backup Strategies against Adversaries. CoRR abs/2102.06632 (2021) - [i7]Edresson Casanova, Christopher Shulby, Eren Gölge, Nicolas Michael Müller, Frederico Santos de Oliveira, Arnaldo Cândido Júnior, Anderson da Silva Soares, Sandra Maria Aluísio, Moacir Antonelli Ponti:
SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model. CoRR abs/2104.05557 (2021) - [i6]Nicolas M. Müller, Simon Roschmann, Konstantin Böttinger:
Defending against Adversarial Denial-of-Service Attacks. CoRR abs/2104.06744 (2021) - [i5]Nicolas M. Müller, Franziska Dieckmann, Pavel Czempin, Roman Canals, Konstantin Böttinger:
Speech is Silver, Silence is Golden: What do ASVspoof-trained Models Really Learn? CoRR abs/2106.12914 (2021) - [i4]Nicolas M. Müller, Karla Markert, Konstantin Böttinger:
Human Perception of Audio Deepfakes. CoRR abs/2107.09667 (2021) - 2020
- [i3]Nicolas Michael Müller, Daniel Kowatsch, Konstantin Böttinger:
Data Poisoning Attacks on Regression Learning and Corresponding Defenses. CoRR abs/2009.07008 (2020) - [i2]Tom Dörr, Karla Markert, Nicolas M. Müller, Konstantin Böttinger:
Towards Resistant Audio Adversarial Examples. CoRR abs/2010.07190 (2020) - 2019
- [i1]Nicolas Michael Müller, Karla Markert:
Identifying Mislabeled Instances in Classification Datasets. CoRR abs/1912.05283 (2019)
Coauthor Index
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