animation in Python, visualizing the infinite, non-repeating nature of pi through dynamic graphics and mathematical patterns. You’ll learn how to use Python to generate digits of π, create smooth ...

Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...

An illustration of multicolored tangle of threads within a small black sphere. A 3D illustration shows DNA packaged into the nucleus, scientists with the 4D Nucleome project are now building accurate ...

🌀Spatial Reasoners is a generalization of Spatial Reasoning Models (SRMs) to new domains, packaged as a reusable library for the research community. You can always start with even_pixels experiment, ...

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 ...

When children assemble puzzles, build block towers, or follow instructions for folding three-dimensional origami figures, they’re using spatial skills—the ability to visualize, manipulate, and make ...

Summary: A new study reveals that the brain rapidly rewires itself to map rewarding experiences like food, even when the location of those rewards changes. Using virtual reality and real-time brain ...

The growing availability of spatial transcriptomics data offers key resources for annotating query datasets using reference datasets. However, batch effects, unbalanced reference annotations, and ...

Abstract: Convolutional neural networks (CNNs) and graph neural networks (GNNs) are two widely used architectures in hyperspectral image (HSI) classification. Most CNN models tend to heavily rely on ...