@article{haider2025relu,title={Injectivity of {ReLU} layers: Tools from frame theory},author={Haider, Daniel and Ehler, Martin and Balazs, Peter},journal={Mathematical Foundations of Machine Learning},volume={1},number={2},year={2025},doi={https://doi.org/10.1007/s44439-025-00003-6},}
Optimal lower Lipschitz bounds for ReLU layers, saturation and phase retrieval
@article{freeman2025lip,title={Optimal lower {L}ipschitz bounds for {ReLU} layers, saturation and phase retrieval},author={Freeman, Daniel and Haider, Daniel},journal={Applied Computational and Harmonic Analysis},volume={80},year={2025},doi={https://doi.org/10.1016/j.acha.2025.101801},}
Invertibility of ReLU-Layers: A Practical Approach
Hannah Eckert, Daniel Haider, Martin Ehler, and 1 more author
In International Joint Conference on Computational Intelligence (NCTA), 2024
@inproceedings{eckert2024relu,author={Eckert, Hannah and Haider, Daniel and Ehler, Martin and Balazs, Peter},title={Invertibility of ReLU-Layers: A Practical Approach},booktitle={International Joint Conference on Computational Intelligence (NCTA)},year={2024},pages={423-429},}
Convex Geometry of ReLU-layers, injectivity on the ball and local reconstruction
@inproceedings{haider2023convrelu,author={Haider, Daniel and Balazs, Peter and Ehler, Martin},booktitle={International Conference on Machine Learning (ICML)},year={2023},title={Convex Geometry of {R}e{LU}-layers, injectivity on the ball and local reconstruction},}
2. Convolution and Stability
Aliasing in Convnets: A Frame theoretic perspective
@article{haider2025aliasing,title={Aliasing in Convnets: A Frame theoretic perspective},author={Haider, Daniel and Lostanlen, Vincent and Ehler, Martin and Holighaus, Nicki and Balazs, Peter},journal={preprint},year={2025},}
@inproceedings{lostanlen2025reshyb,title={{Residual Hybrid Filterbanks}},author={Lostanlen, Vincent and Zhang, Xiran and Haider, Daniel and Lagrange, Mathieu and Ehler, Martin and Balazs, Peter},booktitle={{IEEE Statistical Signal Processing Workshop (SSP)}},year={2025},}
@article{haider2023randomconvnet,author={Haider, Daniel and Lostanlen, Vincent and Ehler, Martin and Balazs, Peter},journal={IEEE Signal Processing Letters},year={2024},volume={31},pages={1084--1088},title={Instabilities in convnets for raw audio},}
(Almost) smooth sailing: Towards numerical stability of neural networks through differentiable regularization of the condition number
@inproceedings{nenov2024smoothsailing,author={Nenov, Rossen and Haider, Daniel and Balazs, Peter},booktitle={2nd Differentiable Almost Everything Workshop at the 41st International Conference on Machine Learning (ICML)},year={2024},title={({A}lmost) smooth sailing: Towards numerical stability of neural networks through differentiable regularization of the condition number},}
3. Audio Processing
ISAC: An Invertible and Stable Auditory Filter Bank with Customizable Kernels for ML Integration
Daniel Haider, Felix Perfler, Peter Balazs, and 2 more authors
In IEEE International Conference on Sampling Theory and Applications (SampTA), 2025
@inproceedings{haider2025isac,author={Haider, Daniel and Perfler, Felix and Balazs, Peter and Hollomey, Clara and Holighaus, Nicki},title={{ISAC}: An Invertible and Stable Auditory Filter
Bank with Customizable Kernels for ML Integration},booktitle={IEEE International Conference on Sampling Theory and Applications (SampTA)},year={2025},}
Hold me tight: Stable encoder/decoder design for speech enhancement
@inproceedings{haider2024holdmetight,author={Haider, Daniel and Perfler, Felix and Lostanlen, Vincent and Ehler, Martin and Balazs, Peter},booktitle={Annual Conference of the International Speech Communication Association (Interspeech)},year={2024},title={Hold me tight: Stable encoder/decoder design for speech enhancement},}
Trainable Signal Encoders that are Robust Against Noise
Peter Balazs, Daniel Haider, Felix Perfler, and 1 more author
In Internoise Conference, 2024
Fitting auditory filterbanks with multiresolution neural networks
@inproceedings{lostanlen2023murenn,author={Lostanlen, Vincent and Haider, Daniel and Han, Han and Lagrange, Mathieu and Balazs, Peter and Ehler, Martin},booktitle={IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)},year={2023},title={Fitting auditory filterbanks with multiresolution neural networks},}
Zeit-Frequenz Darstellungen und Deep Learning
Daniel Haider, Peter Balazs, Nicki Holighaus, and 1 more author
In Tagungsband der 47ten Jahrestagung fuer Akustik (DAGA), Vienna, Austria, 2021
@inproceedings{haider2021daga,author={Haider, Daniel and Balazs, Peter and Holighaus, Nicki and Gutscher, Lorenz},booktitle={Tagungsband der 47ten Jahrestagung fuer Akustik (DAGA), Vienna, Austria},year={2021},pages={29--32},title={Zeit-{F}requenz {D}arstellungen und {D}eep {L}earning},}
@inproceedings{haider2021phasescat,author={Haider, Daniel and Balazs, Peter and Holighaus, Nicki},booktitle={European Signal Processing Conference (EUSIPCO), Dublin, Ireland},year={2021},pages={6--10},title={Phase-based signal representations for scattering},}
Master Thesis: Aspects of Time-Frequency Scattering and Towards Phase Scattering
@mastersthesis{haider2019master,author={Haider, Daniel},institution={University of Vienna},title={Master Thesis: Aspects of Time-Frequency Scattering and Towards Phase Scattering},year={2019},}
Extraction of Rhythmical Features with the Gabor Scattering Transform
@inproceedings{haider2019gabrhythm,author={Haider, Daniel and Balazs, Peter},booktitle={International Symposium on Computer Music Multidisciplinary Research (CMMR), Marseille, France},year={2019},pages={916--923},title={Extraction of Rhythmical Features with the {G}abor Scattering Transform},}
5. Gabor Analysis
Double preconditioning for Gabor frame operators: Algebraic, functional analytic and numerical aspects
Hans G. Feichtinger, Peter Balazs, and Daniel Haider
@article{feichtinger2023double,title={Double preconditioning for {G}abor frame operators: Algebraic, functional analytic and numerical aspects},author={Feichtinger, Hans G. and Balazs, Peter and Haider, Daniel},journal={Applied and Computational Harmonic Analysis},volume={66},pages={101--137},year={2023},}
