Publications related to Comparison of Subword Segmentation Methods for Open-vocabulary ASR using a Difficulty Metric

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Paul Mos, Yang Lin

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

Berlin2024

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

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The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

EPFL2024

Aggregating Spatial and Photometric Context for Photometric Stereo

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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

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The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

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Generalization of Scaled Deep ResNets in the Mean-Field Regime

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Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

Intraday solar irradiance forecasting using public cameras

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In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

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Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power.Simultaneously, a critical pain point arises as several computer vision applications are deployed ...

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Deep Learning Theory Through the Lens of Diagonal Linear Networks

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In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Comparison of Subword Segmentation Methods for Open-vocabulary ASR using a Difficulty Metric

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Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Aggregating Spatial and Photometric Context for Photometric Stereo

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Intraday solar irradiance forecasting using public cameras

Random matrix methods for high-dimensional machine learning models

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Aggregating Spatial and Photometric Context for Photometric Stereo

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Intraday solar irradiance forecasting using public cameras

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Random matrix methods for high-dimensional machine learning models