Advances in Bias-aware Recommendation on the Web

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Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to catheteri ...

Estimating ecosystem-atmosphere fluxes such as evapotranspiration (ET) in a robust manner and at a global scale remains a challenge. Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary ...

This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. The algorithm retains high ...

Two design studios were successively taught in two schools of architecture: one at the Harvard Graduate School of Design (GSD) and the other at the Swiss Federal Institute of Technology in Lausanne (EPFL) in Lausanne, Switzerland, based on "A Global Morato ...

To retrieve Surface Solar Radiation (SSR) from satellite images, a baseline reflectance of the observed ground in clear-sky conditions, also called background reflectance, is necessary to distinguish atmospheric absorption and scattering effects from surfa ...

This book has been designed for instructors in higher education or adult training who wish to develop a new course or revise an existing one. It adopts a practical, visual, and modular approach based on the principle of constructive alignment. At its heart ...

This paper introduces a novel architecture for Quantum Graph Neural Networks, which is significantly different from previous approaches found in the literature. The proposed approach produces similar outcomes with respect to previous models but with fewer ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

The digitization of 3D deformable objects remains a significant challenge in computer graphics and vision, particularly in the accurate modeling of garments. Garments exhibit complex shape variability, non-rigid deformations, and frequent self-occlusion, m ...

This study integrates deep learning and geospatial analysis to enhance soil loss estimation in the Moulouya Watershed, a region prone to erosion due to diverse topography and climatic conditions. Traditional models like the Universal Soil Loss Equation (US ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Given a ground-level query image and a geo-referenced aerial image that covers the query’s local surroundings, fine-grained cross-view localization aims to estimate the location of the ground camera inside the aerial image. Recent works have focused on dev ...

Superconducting electronics provide us with cryogenic digital circuits that can rival established technologies in performance and energy consumption. Today, the lack of tools for the design of large-scale integrated superconducting circuits is a major obst ...

Jointly estimating hand and object shape facilitates the grasping task in human-to-robot handovers. Relying on handcrafted prior knowledge about the geometric structure of the object fails when generalising to unseen objects, and depth sensors fail to dete ...

We conduct two survey experiments to study which information people choose to consume and how it affects their beliefs. In the first experiment, respondents choose between optimistic and pessimistic article headlines related to the COVID-19 pandemic and ar ...

Automatic speech recognition (ASR) systems are well known to perform poorly on dysarthric speech. Previous works have addressed this by speaking rate modification to reduce the mismatch with typical speech. Unfortunately, these approaches rely on transcrib ...

The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is mana ...

A robust anomaly detection mechanism should possess the capability to effectively remediate anomalies, restoring them to a healthy state, while preserving essential healthy information. Despite the efficacy of existing generative models in learning the und ...

The global construction industry contributes to 37% of carbon emissions associated to both building operations and construction. To help achieve the net-zero targets set by 2050, it is mandated to achieve a 50% reduction in carbon emissions by 2030. As we ...

Advances in Bias-aware Recommendation on the Web

Chat with Graph Search

Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population

On the added value of sequential deep learning for the upscaling of evapotranspiration

Enhancing skin lesion classification: a CNN approach with human baseline comparison

Teaching Not To

Retrieval of Surface Solar Radiation through Implicit Albedo Recovery from Temporal Context

Course Design - A Visual and Modular Approach

A Study on Quantum Graph Neural Networks Applied to Molecular Physics

Exploiting the Signal-Leak Bias in Diffusion Models

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Neural Garment Modeling

Application of Deep Learning and Geospatial Analysis in Soil Loss Risk in the Moulouya Watershed, Morocco

Machine learning-aided generative molecular design

Adapting Fine-Grained Cross-View Localization to Areas Without Fine Ground Truth

Technology-Aware Logic Synthesis for Superconducting Electronics

Stereo Hand-Object Reconstruction for Human-to-Robot Handover

Biases in Information Selection and Processing: Survey Evidence from the Pandemic

Unsupervised Rhythm and Voice Conversion of Dysarthric to Healthy Speech for ASR

Models implemented in the methodological approach to design the initial STEP first wall contour

Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet

An explorative method to support design decisions based on carbon constraints and daylight sufficiency needs