MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

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In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

The application of kernel-based Machine Learning (ML) techniques to discrete choice modelling using large datasets often faces challenges due to memory requirements and the considerable number of parameters involved in these models. This complexity hampers ...

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Decentralized learning (DL) is an emerging approach that enables nodes to collaboratively train a machine learning model without sharing raw data. In many application domains, such as healthcare, this approach faces challenges due to the high level of hete ...

Cities are facing unprecedented challenges to their environments and residents due to continuous growth, including urban overheating, daylight accessibility, noise, and air pollution. This requires a holistic approach to the research and implementation of ...

Current transformer-based skeletal action recognition models tend to focus on a limited set of joints and low-level motion patterns to predict action classes. This results in significant performance degradation under small skeleton perturbations or changin ...

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimen ...

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their u ...

MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

Chat with Graph Search

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling

Residual-based attention in physics-informed neural networks

Fair Decentralized Learning

A multidomain approach to neighbourhood typology for urban environmental studies

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Orchestrating chromosome conformation capture analysis with Bioconductor

Network time series forecasting in photovoltaics power production

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Data set for control of Ge island coalescence for the formation of nanowires on silicon

The multimodality cell segmentation challenge: toward universal solutions

Meta-learning to address diverse Earth observation problems across resolutions

In-Sensor Passive Speech Classification with Phononic Metamaterials