Spatial Temporal Graph Convolution Networks (ST-GCNs) have been proposed to embed spatio-temporal graphs. However, these networks used the Euclidean space as the embedding space which does not exploit ...

Lymph node stroma model development. We sought to develop a model of immune cell egress from the lymph node. Credit: APL Bioengineering (2025). DOI: 10.1063/5.0247363 ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

Graph technology is allowing pharma to model data in a way that offers invaluable insights for marketing, R&D and compliance teams alike. Google, Facebook and LinkedIn are among those utilising ...

Background Chronic inflammation and elevated reactive oxygen species are key contributors to hepatocellular carcinoma (HCC) ...

in remove_getattr_nodes () in torchir_passes.py. The issue is that the flatten_graph_output_values pass adds my_constant_output and my_constant_output2 to the graph output. Then in ...

The model’s applicability is confirmed across ten different temperature datasets. Consequently, the proposed GlobalTempNet, coupled with the EGNT process, emerges as a robust, reliable, and ...

Adds two nodes which allow using Fooocus inpaint model. It's a small and flexible patch which can be applied to your SDXL checkpoints and will transform them into an inpaint model. This model can then ...