Related papers: The Distributed and Unified Numerics Environment (…
Medical image segmentation plays a pivotal role in automated diagnostic and treatment planning systems. In this work, we present DAUNet, a novel lightweight UNet variant that integrates Deformable V2 Convolutions and Parameter-Free…
Computational notebooks, while essential for data science, are limited by their one-dimensional interface, which poorly aligns with non-linear developer workflows and complicates collaboration and human-AI interaction. In this work, we…
We present a numerical framework for deep neural network (DNN) modeling of unknown time-dependent partial differential equations (PDE) using their trajectory data. Unlike the recent work of [Wu and Xiu, J. Comput. Phys. 2020], where the…
Wearable devices are revolutionizing personal technology, but their usability is often hindered by frequent charging due to high power consumption. This paper introduces Distributed Neural Networks (DistNN), a framework that distributes…
The recent success of Deep Neural Networks (DNNs) has drastically improved the state of the art for many application domains. While achieving high accuracy performance, deploying state-of-the-art DNNs is a challenge since they typically…
Due to its ability to generate millions of particles, massively detailed scenes and confusing artificial illumination with reality, the version 5 of Unreal Engine promises unprecedented industrial applications. The paradigms and aims of…
Cloud computing has grown in importance in recent years which has led to a significant increase in Data Centre (DC) network requirements. A major driver of this change is virtualisation, which allows computing resources to be deployed on a…
Document Image Enhancement (DIE) serves as a critical component in Document AI systems, where its performance substantially determines the effectiveness of downstream tasks. To address the limitations of existing methods confined to…
Deep neural networks (DNNs) have become one of the enabling technologies in many safety-critical applications, e.g., autonomous driving and medical image analysis. DNN systems, however, suffer from various kinds of threats, such as…
Machine learning, especially deep learning is gaining much attention due to the breakthrough performance in various cognitive applications. Recently, neural networks (NN) have been intensively explored to model partial differential…
In this paper I present a novel type of Topology and Weight Evolving Artificial Neural Network (TWEANN) system called Modular Discover & eXplore Neural Network (DXNN). Modular DXNN utilizes a hierarchical/modular topology which allows for…
Recent advances in Deep Neural Networks (DNNs) have demonstrated outstanding performance across various domains. However, their large size is a challenge for deployment on resource-constrained devices such as mobile, edge, and IoT…
The importance of cloud computing has grown over the last years, which resulted in a significant increase of Data Center (DC) network requirements. Virtualisation is one of the key drivers of that transformation and enables a massive…
Ultra-dense network (UDN) is a promising technology to further evolve wireless networks and meet the diverse performance requirements of 5G networks. With abundant access points, each with communication, computation and storage resources,…
The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino experiment. In addition to GeV-scale oscillation measurements ($\delta_{CP}$, $\theta_{23}$ octant, mass ordering), DUNE features a low-energy…
The DUNE IDR describes the proposed physics program and technical designs of the DUNE far detector modules in preparation for the full TDR to be published in 2019. It is intended as an intermediate milestone on the path to a full TDR,…
The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay -- these mysteries at the forefront of particle…
Model compression is essential in the deployment of large Computer Vision models on embedded devices. However, static optimization techniques (e.g. pruning, quantization, etc.) neglect the fact that different inputs have different…
The DUNE IDR describes the proposed physics program and technical designs of the DUNE far detector modules in preparation for the full TDR to be published in 2019. It is intended as an intermediate milestone on the path to a full TDR,…
The release of GENIE v3.0.0 was a major milestone in the long history of the GENIE project, delivering several alternative comprehensive neutrino interaction models, improved charged-lepton scattering simulations, a range of beyond the…