New weight tracking feature enables users to log weight, set goals, and visualize progress through monthly and yearly ...
Due to the significant amount of time and expertise needed for manual segmentation of the brain cortex from magnetic resonance imaging (MRI) data, there is a substantial need for efficient and ...
Abstract: Graph Neural Networks (GNNs) have gained popularity as an efficient choice for learning on graph-structured data. However, most methods are node or graph-centered, often overlooking valuable ...
According to @godofprompt, leading AI engineers at OpenAI, Anthropic, and Microsoft are shifting from traditional RAG (Retrieval-Augmented Generation) systems to graph-enhanced retrieval methods, ...
According to God of Prompt (@godofprompt), top engineers at AI companies such as OpenAI, Anthropic, and Microsoft are moving beyond basic Retrieval-Augmented Generation (RAG) by prioritizing ...
Graphene, a single sheet of carbon atoms arranged in a honeycomb lattice, is known for its exceptional strength, flexibility and conductivity. However, despite holding the world record for ...
DeH4R unifies graphgrowing dynamics with graph-generating efficiency through a decoupling strategy, effectively harnessing their complementary strengths, which offers great flexibility and is able to ...
ABSTRACT: This research investigates the impact of the road network topological structure on facility location modeling. We create four types of road networks, i.e., the radial, the grid, the ring, ...
Currently, PyTorch supports CUDA Graph features under torch.cuda namespace, providing capture, replay functionality via C++ CUDAGraph implementation. This RFC proposes to generalize the existing graph ...
College of Artificial Intelligence, Tianjin Normal University, Tianjin 300387, China Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin ...
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