Open Knowledge Repository - World Bank

Fine-Scale Spatial Disaggregation of Statistical Data via Graph Neural Networks

Fine-grained spatial data are critical for informed decision-making in domains ranging from economic planning to ...

The Money Trail That Never Stops: Understanding Daisy Chains in Payment Networks

Daisy chains are different. Their signal is structural. What matters is not one transaction, but the sequence. Imagine money ...
Directions Magazine

Crypto Chart Patterns: How to Apply Them to Your Trading Strategy

Crypto chart patterns are recurring formations on a chart created by changes in cryptocurrency price over time. In technical ...
Hosted on MSN

Graphing a vertical linear equation from a table

👉 Learn how to graph linear equations from the table of points. When given the table of points of a linear equation, we plot the x and y coordinates of the given table on the Cartesian plane and join ...
Hosted on MSN

Graphing a linear equation in slope intercept form

👉 Learn how to graph linear equations written in slope intercept form. When given a linear equation in slope intercept form, (i.e. in the form y = mx + c, where m is the slope and c is the ...
IEEE

Toward High-Accuracy and Low-Latency Group Vehicle Trajectory Prediction With Linear UNet-Enhanced Fully Connected Spatial–Temporal Graph Neural Network

Abstract: Group vehicle trajectory prediction (GVTP) is important for analyzing the traffic states and optimizing the traffic management. However, existing studies have performance bottlenecks in the ...
IEEE

JEDI-Linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs

Abstract: Graph Neural Networks (GNNs), particularly Interaction Networks (INs), have shown exceptional performance for jet tagging at the CERN High-Luminosity Large Hadron Collider (HL-LHC). However, ...
eLife

A network regularized linear model to infer spatial expression pattern for single cell

The development of glmSMA represents a valuable advancement in spatial transcriptomics analysis, offering a mathematically robust regression-based approach that achieves higher-resolution mapping of ...