19 citations · 19 across the 5 of their papers we have counts for
5 papers
Learnable Adaptive Time-Frequency Representation via Differentiable Short-Time Fourier Transform
Maxime Leiber, Yosra Marnissi, Axel Barrau +2
The short-time Fourier transform (STFT) is widely used for analyzing non-stationary signals. However, its performance is highly sensitive to its parameters, and manual or heuristic…
Differentiable short-time Fourier transform with respect to the hop length
Maxime Leiber, Yosra Marnissi, Axel Barrau +1
In this paper, we propose a differentiable version of the short-time Fourier transform (STFT) that allows for gradient-based optimization of the hop length or the frame temporal po…
Differentiable adaptive short-time Fourier transform with respect to the window length
Maxime Leiber, Yosra Marnissi, Axel Barrau +1
This paper presents a gradient-based method for on-the-fly optimization for both per-frame and per-frequency window length of the short-time Fourier transform (STFT), related to pr…
A differentiable short-time Fourier transform with respect to the window length
Maxime Leiber, Axel Barrau, Yosra Marnissi +1
In this paper, we revisit the use of spectrograms in neural networks, by making the window length a continuous parameter optimizable by gradient descent instead of an empirically t…
A Variational Bayesian Approach for Image Restoration. Application to Image Deblurring with Poisson-Gaussian Noise
Yosra Marnissi, Yuling Zheng, Emilie Chouzenoux +1
In this paper, a methodology is investigated for signal recovery in the presence of non-Gaussian noise. In contrast with regularized minimization approaches often adopted in the li…