STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
Single neurons in mouse sensorimotor cortex are organized by their activity features into distinct subpopulations with area-spanning footprints whose boundaries align closely with anatomical and ...
Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...
Abstract: In this paper, we test whether Multimodal Large Language Models (MLLMs) can match human-subject performance in tasks involving the perception of properties in network layouts. Specifically, ...
Docker eliminates dependency hell (pycapnp builds, Julia packages, CUDA) and makes the pipeline reproducible. GPU training in Docker requires nvidia-container-toolkit ...
Abstract: Event cameras form a fundamental foundation for visual perception in scenes characterized by high speed and a wide dynamic range. Although deep learning techniques have achieved remarkable ...
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