A dual-graph deep learning network that hard-codes petroleum physics alongside learned statistics cuts oil production prediction error to about 20 percent, far outperforming conventional models.
A new heterogeneous graph Kolmogorov-Arnold network called HG-KAN predicts how water injected into layered oil reservoirs ...
NVIDIA on October 14, 2026, unveiled cuPotential, a new CUDA-X library that developers can use to build AI agents simulating ...
"Gemini 4 Argon handles complex tasks reliably, from 3D games to rich animations. In Figma Make, it helps teams turn their ...
While reading their proof, important note: The cubic family of L-functions appear to be essential for the proof, even for the corollary to the Riemann zeta function ...
png, 503 KB png, 540.91 KB png, 478.67 KB png, 454.58 KB zip, 34.14 MB A collection of PowerPoints covering both Unit 1 and 2 of the MATHEMATICS METHODS curriculum. Each PPTX is aligned to an exercise ...
Agent bindings for Python function apps let you add agentic behaviors to existing functions. When the function runs, the extension constructs an Agent from Markdown instructions and injects it into ...
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