Neural active manifolds: nonlinear dimensionality reduction for uncertainty quantification
arxiv.org·2d
🗺️UMAP
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Toward a Compressed Core of Human Knowledge: The High-Dimensional Vector Network for AI
🔢Embeddings
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Unlocking Neural Network Secrets: The Geometric Awakening by Arvind Sundararajan
🔢Embeddings
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Hidden network preserved in Slide-tags data allows reference-free spatial reconstruction
nature.com·2d
🗺️Spatial Transcriptomics
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Can-t stop till you get enough
🗂️AnnData
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Weak-To-Strong Generalization
lesswrong.com·18h
📊Empirical Bayes
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Developing a Multi-task Ensemble Geometric Deep Network for Supply Chain Sustainability and Risk Management
arxiv.org·2d
🗺️UMAP
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<p>**Abstract:** Accurate characterization of geothermal fluids and subsurface reservoirs is critical for efficient and sustainable energy extraction. Tradition...
freederia.com·3h
⛰️Gradient Descent
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Reinforcement learning driven adaptive graph construction for fault diagnosis of chemical processes
sciencedirect.com·1d
🔗Markov Chains
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Clone Deterministic 3D Worlds with Geometrically-Regularized World Models
arxiv.org·2d
🦠Whole cell model
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Contribution-Guided Asymmetric Learning for Robust Multimodal Fusion under Imbalance and Noise
arxiv.org·2d
📐Matrix Factorization
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Curly Flow Matching for Learning Non-gradient Field Dynamics
arxiv.org·2d
⛰️Gradient Descent
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