Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather ...
Neural Texture Compression (NTC) could be a game-changer on par with DLSS if it can reduce the VRAM requirement for textures ...
Morning Overview on MSN
Nvidia demo shows neural texture compression can cut VRAM use by up to 85%
Nvidia researchers have proposed a neural network-based method for compressing material textures that, in results reported in ...
The advent of high-density recording technologies, such as Neuropixels and large-scale calcium imaging, has provided an unprecedented look into the ...
Researchers at Skoltech have proposed a new approach to training neural networks for wave propagation in absorbing media. The ...
The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...
AI systems are "trained" using massive datasets, and the quality of this data determines the model's performance. AI can ...
The rise of AI has brought an avalanche of new terms and slang. Here is a glossary with definitions of some of the most ...
How can AI stabilize the power grid? New research uses biomimetic neural networks to manage the uncertainty of solar and wind energy, reducing hardware costs and preventing blackouts.
The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...
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