Toward a Collective Agenda on AI for Earth Science Data Analysis

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Computational Imaging (CI) is the field concerned with reconstructing images of some quantity of interest from a finite number of measurements. It is pervasive in science and engineering problems by enabling the reconstruction of images from a variety of m ...

Uncovering the neural architectures that enable robust and flexible motor control is a fundamental challenge in neuroscience. Understanding the neural circuitry organisation at a cellular level is crucial for advancing our knowledge and developing interven ...

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

This paper investigates the potential impact of deep generative models on the work of creative professionals, specifically focusing on fashion design. We argue that current generative modeling tools lack critical features that would make them useful creati ...

Currently, the indoor thermal environment in many buildings is controlled by conventional control techniques that maintain the indoor temperature within a prescribed deadband. The latest research provides evidence that more dynamic variations of the indoor ...

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be use ...

Over the last decades, the progress made in the generation of laser pulses shorter than a picosecond (10^-12 s) has allowed us to reach extreme optical power intensities exceeding 10^15 W cm^-2. This tremendous power has triggered an abundance of original ...

We present numerical simulations and experimental results of the self-modulation of a long proton bunch in a plasma with linear density gradients along the beam path. Simulation results agree with the experimental results reported [F. Braunmller, T. Nechae ...

The deployment of robots for Gas Source Lo- calization (GSL) tasks in hazardous scenarios significantly reduces the risk to humans and animals. Gas sensing using mobile robots focuses primarily on simplified scenarios, due to the complexity of gas dispersi ...

The aim of this thesis is to implement, analyze and improve the selected low noise clock generation and distribution techniques for ADC implementations. The thesis is divided into two parts. The first part focuses on the sampling phase generation and distr ...

Locomotion is based on a sophisticated interaction among the environment, the musculoskeletal system, the spinal cord, and the brain locomotor areas. Quality of life is strongly related to the proper capability of this movement. However, many pathologies, ...

This paper presents a novel simulation approach for generating synthetic households, addressing several literature gaps from the methodological viewpoint. The generation of hierarchical datasets such as complete households is challenging since it must guar ...

Numerical simulations are of a tremendous help to understand the growth of non-linear cosmological structures and how they lead to the formation of galaxies. In recent years, with the goal of improving their prediction power, new hydrodynamical techniques ...

Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered a ...

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

The automatic recognition of food on images has numerous interesting applications, including nutritional tracking in medical cohorts. The problem has received significant research attention, but an ongoing public benchmark on non-biased (i.e., not scraped ...

Harnessing quantum randomness for the generation of random numbers is an important concept crucial for information security and many other computer-related applications. Quantum random number generators (QRNGs) are evolving from bulky, slow, and expensive ...

Implicit neural representations (INRs) have recently emerged as a promising alternative to classical discretized representations of signals. Nevertheless, despite their practical success, we still do not understand how INRs represent signals. We propose a ...

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

Toward a Collective Agenda on AI for Earth Science Data Analysis

Chattez avec Graph Search

Computational Imaging: a Multi-Facet Perspective

Uncovering neural architectures enabling robust and flexible motor control in Drosophila

A new age in protein design empowered by deep learning

Fashioning the Future: Unlocking the Creative Potential of Deep Generative Models for Design Space Exploration

Dynamic indoor thermal environment using Reinforcement Learning-based controls: Opportunities and challenges

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Simulated Learners in Educational Technology: A Systematic Literature Review and a Turing-like Test

In situ monitoring of femtosecond laser-induced modifications in dielectrics

Simulation and experimental study of proton bunch self-modulation in plasma with linear density gradients

Towards Efficient Gas Leak Detection in Built Environments: Data-Driven Plume Modeling for Gas Sensing Robots

Low Noise Clock Generation: Modeling, Analysis and Implementation

Investigating the neuromechanical control of healthy gait modulation and pathological gaits observed in cerebral palsy using neuromuscular simulations

Divide-and-conquer one-step simulator for the generation of synthetic households

Towards Efficient and Accurate Numerical Simulations of Galaxies using Task-based Parallelism and Application to Dwarf Galaxies

Deep Learning for the Earth Sciences: A Comprehensive Approach to Remote Sensing, Climate Science, and Geosciences

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

The Food Recognition Benchmark: Using Deep Learning to Recognize Food in Images

Random flip-flop: adding quantum randomness to digital circuits for improved cyber security, artificial intelligence and more

A Structured Dictionary Perspective on Implicit Neural Representations

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models