Risk governance and the rise of deepfakes

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Niobium nitride (NbN) is a particularly promising material for quantum technology applications, as it shows the degree of reproducibility necessary for large-scale superconducting circuits. We demonstrate that resonators based on NbN thin films present a o ...

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

Aluminium is the second most widely used metal in the world, with a variety of applications ranging from transportation to food packaging and construction. While many aluminium producers target increased utilization of recycled aluminium to produce rolled ...

Diffusion Magnetic Resonance Imaging (dMRI) is a powerful non-invasive method for studying white matter tracts of the brain. However, accurate microstructure estimation with fiber orientation distribution (FOD) using existing computational methods requires ...

In recent years, the remarkable progress in facial manipulation techniques has raised social concerns due to their potential malicious usage and has received considerable attention from both industry and academia. While current deep learning-based face for ...

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...

Deep learning (DL) has been wildly successful in practice, and most of the state-of-the-art machine learning methods are based on neural networks (NNs). Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of ...

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...

Thin-film lithium niobate (LNO) has been identified as a promising material platform for enabling high electromechanical coupling and low-loss piezoelectric resonators for filtering applications. In this work, the design and fabrication of fundamental shea ...

This work introduces a diffusion model for molecule generation in 3D that is equivariant to Euclidean transformations. Our E(3) Equivariant Diffusion Model (EDM) learns to denoise a diffusion process with an equivariant network that jointly operates on bot ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century on. However, the plurality of formats and the natural variability of historical data make their extraction arduous and ...

Risk governance and the rise of deepfakes

Chattez avec Graph Search

NbN films with high kinetic inductance for high-quality compact superconducting resonators

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Decarbonizing The Production of Primary Aluminium Using Renewable Resource

Robust Estimation of the Microstructure of the Early Developing Brain Using Deep Learning

Improving Deepfake Detectors against Real-world Perturbations with Amplitude-Phase Switch Augmentation

Deep Learning Generalization with Limited and Noisy Labels

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Virtual metrology applied to milling process

Deep Learning Meets Sparse Regularization

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

DISCO: Distilling Counterfactuals with Large Language Models

Optimization of Edge Profile for Improved Anti-Resonance Quality Factor in Lithium Niobate SH0 Resonators

Equivariant Diffusion for Molecule Generation in 3D

Caching and Neutrality

An end-to-end pipeline for historical censuses processing