Abstract: Graph Neural Networks (GNNs) show great power in Knowledge Graph Completion (KGC) as they can handle non-Euclidean graph structures and do not depend on the specific shape or topology of the ...

This important study demonstrates that a peri-nuclear actomyosin network, present in some types of human cells, facilitates kinetochore-spindle attachment of chromosomes in unfavorable locations - ...

Explore the leading data orchestration platforms for 2026 with quick comparisons, practical selection tips, and implementation guidance to keep your data pipelines reliable and scalable.

Abstract: Graph pooling technique as the essential component of graph neural networks has gotten increasing attention recently and it aims to learn graph-level representations for the whole graph.

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential across disciplines. These ...

Plotly announces major update to AI-native data analytics platform Plotly Studio, turning data into production-ready ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account the laws of physics—using Newton's third law. Their research is published ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

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Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...