Tag: artificial neural networks
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C-voting: Boost Test-Time Accuracy Without Energy Functions
Discover C-voting, a confidence-based test-time voting method that improves neural model accuracy without explicit energy functions in reasoning tasks.
Spectral Entropy Collapse Signals Delayed Grokking in ML
Discover how spectral entropy collapse predicts delayed generalisation in grokking, revealing key insights into machine learning model behavior and archite...
Selective Measurement Boosts Forward-Forward Learning Accuracy
Discover how selective measurement and adaptive sparsity improve Forward-Forward learning, achieving up to 87.1% accuracy on Fashion-MNIST datasets.
Wolkowicz-Styan Bound on Hessian Spectrum in Neural Nets
Discover the Wolkowicz-Styan upper bound on Hessian eigenspectrum for cross-entropy loss in smooth nonlinear neural networks, enhancing deep learning analy...
Generative Modeling for Precise Molecular Structure Retrieval
Discover how generative modeling and Coulomb explosion imaging enable accurate real-time molecular structure retrieval with advanced neural networks.