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Found 8 papers, 5 papers with code
Instabilities in Convnets for Raw Audio
Numerical simulations align with our theory and suggest that the condition number of a convolutional layer follows a logarithmic scaling law between the number and length of the filters, which is reminiscent of discrete wavelet bases.
Fitting Auditory Filterbanks with Multiresolution Neural Networks
Waveform-based deep learning faces a dilemma between nonparametric and parametric approaches.
Convex Geometry of ReLU-layers, Injectivity on the Ball and Local Reconstruction
The paper uses a frame-theoretic setting to study the injectivity of a ReLU-layer on the closed ball of $\mathbb{R}^n$ and its non-negative part.
visClust: A visual clustering algorithm based on orthogonal projections
The code is made available on GitHub and straightforward to use.
Blood vessel segmentation in en-face OCTA images: a frequency based method
The results underline the visual evaluation.
An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans
Supervised deep learning models trained with standard loss functions are usually able to characterize only the most common disease appeareance from a training set, resulting in suboptimal performance and poor generalization when dealing with unseen lesions.
On orthogonal projections for dimension reduction and applications in augmented target loss functions for learning problems
In two supervised learning problems, clinical image segmentation and music information classification, the application of our proposed augmented target loss functions increase the accuracy.
The Algebraic Approach to Phase Retrieval and Explicit Inversion at the Identifiability Threshold
We study phase retrieval from magnitude measurements of an unknown signal as an algebraic estimation problem.
