Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study
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At initialization, artificial neural networks (ANNs) are equivalent to Gaussian processes in the infinite-width limit [12, 9], thus connecting them to kernel methods. We prove that the evolution of an ANN during training can also be described by a kernel: ...
Clinical applications, such as image-guided surgery and noninvasive diagnosis, rely heavily on multi-modal images. Medical image fusion plays a central role by integrating information from multiple sources into a single, more understandable output. We prop ...
We propose to use neural networks for simultaneous detection and localization of multiple sound sources in human-robot interaction. In contrast to conventional signal processing techniques, neural network-based sound source localization methods require few ...
System modeling and simulation plays a crucial role in the engineering of large and complex systems from various fields, such as industrial automation or power systems. In this paper, we propose a method that can be used to easily deploy high fidelity simu ...
Uncertainty in deep learning has recently received a lot of attention in research. While stateof- the-art neural networks have managed to break many benchmarks in terms of accuracy, it has been shown that by applying minor perturbations to the input data, ...
The Generalised Command Response (GCR) model is a time-local model of intonation that has been shown to lend itself to (cross-language) transfer of emphasis. In order to generalise the model to longer prosodic sequences, we show that it can be driven by a ...
Novel Deep Neural Network (DNN) accelerators based on crossbar arrays of non-volatile memories (NVMs)-such as Phase-Change Memory or Resistive Memory-can implement multiply-accumulate operations in a highly parallelized fashion. In such systems, computatio ...
We propose to combine recent Convolutional Neural Networks (CNN) models with depth imaging to obtain a reliable and fast multi-person pose estimation algorithm applicable to Human Robot Interaction (HRI) scenarios. Our hypothesis is that depth images conta ...
In this work, we address the problem of query by example spoken term detection (QbE-STD) in zero-resource scenario. State of the art solutions usually rely on dynamic time warping (DTW) based template matching. In contrast, we propose here to tackle the pr ...
We propose a novel multi-task neural network-based approach for joint sound source localization and speech/non-speech classification in noisy environments. The network takes raw short time Fourier transform as input and outputs the likelihood values for th ...