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Found 6 papers, 1 papers with code
Collective Knowledge Graph Completion with Mutual Knowledge Distillation
Knowledge graph completion (KGC), the task of predicting missing information based on the existing relational data inside a knowledge graph (KG), has drawn significant attention in recent years.
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models
The new approach is tested on a high-dimensional CFD application of a two-phase liquid flow with non-linear observation operators that current Latent Assimilation methods can not handle.
A Scalable Inference Method For Large Dynamic Economic Systems
The nature of available economic data has changed fundamentally in the last decade due to the economy's digitisation.
Correcting public opinion trends through Bayesian data assimilation
Traditional survey polling remains the most popular estimation technique, despite its cost and time intensity, measurement errors, lack of real-time capabilities and lagged representation of public opinion.
Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation
We propose a new 'Bi-Reduced Space' approach to solving 3D Variational Data Assimilation using Convolutional Autoencoders.
Data Assimilation in the Latent Space of a Neural Network
There is an urgent need to build models to tackle Indoor Air Quality issue.
