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AI Researchers Are Confronting the Gap Between Neural Network Power and True Generalization
In 2026, neural networks are achieving unprecedented capabilities across industries, yet large-scale tests reveal persistent struggles with generalization. Researchers are exploring adaptive ...
ThousandEyes released its list of the 11 most notable Internet outages and application issues of 2025, along with recommendations to help network teams improve resilience.
In 2026, AI research is moving beyond raw scaling to focus on efficiency, adaptability, and operational robustness. Advances in architectures, benchmarks, and conferences reflect a growing emphasis on ...
Abstract: Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assumption ...
Abstract: Neural operators have emerged as a powerful tool for learning mappings between function spaces, particularly for solving partial differential equations (PDEs). This study introduces a novel ...
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