The authors have performed a potentially valuable new kind of analysis in connectomics, mapping to an interesting developmental problem of synaptic input to sensory neurons. While the analysis itself ...

Graph Neural Networks (GNNs) have demonstrated strong potential for identifying software vulnerabilities by leveraging the structured representation of code as graphs. In this paper, we propose a ...

Abstract: Understanding and interpreting complex coupled systems remains one of the biggest challenges in the world. Examples of these applications range from industrial manufacturing to the temporal ...

This is the official implementation of Nabla-R2D3, which is a highly effective and sample-efficient reinforcement learning alignment framework for 3D-native diffusion models using pure 2D rewards.

GraphFlow ===== C++/CUDA library for deep learning with dynamic computation graphs and automatic differentiation. Includes high-performance tensor and matrix ops (CPU and CUDA) and reference ...