Bayesian Neural Networks vs. Mixture Density Networks: Theoretical and Empirical Insights for Uncertainty-Aware Nonlinear Modeling
arxiv.org·1d
🧮Kolmogorov Bounds
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Stochastic computing
scottlocklin.wordpress.com·3h
🏴Scottish Computing
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A mathematical certification for positivity conditions in Neural Networks with applications to partial monotonicity and Trustworthy AI
arxiv.org·16h
🔍Vector Forensics
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Optimal Information Combining for Multi-Agent Systems Using Adaptive Bias Learning
arxiv.org·16h
🧮Kolmogorov Bounds
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Neural active manifolds: nonlinear dimensionality reduction for uncertainty quantification
arxiv.org·16h
🌀Riemannian Computing
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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·16h
📊Rate-Distortion Theory
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Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation
arxiv.org·2d
📊Quantization
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Unlocking Neural Network Secrets: The Geometric Awakening by Arvind Sundararajan
🌀Differential Geometry
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Empirical Bayesian Multi-Bandit Learning
arxiv.org·16h
🧮Kolmogorov Bounds
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Uncertainty-Aware Diagnostics for Physics-Informed Machine Learning
arxiv.org·16h
🧮Kolmogorov Bounds
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Resource-Efficient and Robust Inference of Deep and Bayesian Neural Networks on Embedded and Analog Computing Platforms
arxiv.org·1d
📊Quantization
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RS-ORT: A Reduced-Space Branch-and-Bound Algorithm for Optimal Regression Trees
arxiv.org·2d
🧮Kolmogorov Bounds
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Quantum Machine Learning for Image Classification: A Hybrid Model of Residual Network with Quantum Support Vector Machine
arxiv.org·2d
📊Quantization
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STAR: A Privacy-Preserving, Energy-Efficient Edge AI Framework for Human Activity Recognition via Wi-Fi CSI in Mobile and Pervasive Computing Environments
arxiv.org·16h
⧗Information Bottleneck
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