Neural active manifolds: nonlinear dimensionality reduction for uncertainty quantification
arxiv.org·1d
🌀Riemannian Computing
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Stochastic computing
scottlocklin.wordpress.com·1d
🏴Scottish Computing
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Empirical Bayesian Multi-Bandit Learning
arxiv.org·1d
🧮Kolmogorov Bounds
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Optimal Information Combining for Multi-Agent Systems Using Adaptive Bias Learning
arxiv.org·1d
🧮Kolmogorov Bounds
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Bayesian Neural Networks vs. Mixture Density Networks: Theoretical and Empirical Insights for Uncertainty-Aware Nonlinear Modeling
arxiv.org·2d
🧮Kolmogorov Bounds
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Unlocking Neural Network Secrets: The Geometric Awakening by Arvind Sundararajan
🌀Differential Geometry
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A mathematical certification for positivity conditions in Neural Networks with applications to partial monotonicity and Trustworthy AI
arxiv.org·1d
🔍Vector Forensics
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Deep Reinforcement Learning Book
🧠Neural Codecs
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Contribution-Guided Asymmetric Learning for Robust Multimodal Fusion under Imbalance and Noise
arxiv.org·1d
📊Rate-Distortion Theory
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Semantic search with embeddings in PHP: a hands-on guide using Neuron AI and Ollama
🧮Vector Embeddings
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Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation
arxiv.org·3d
📊Quantization
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Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning
arxiv.org·1d
🧮Kolmogorov Bounds
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