Ubuntu Blog: Edge Networking gets smarter: AI and 5G in action
ubuntu.com·7h
📦HDF5
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Masked Softmax Layers in PyTorch
⛰️Gradient Descent
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Interpretable radiomics-based machine learning model for differentiating glioblastoma from primary central nervous system lymphoma using contrast-enhanced T1-we...
nature.com·1d
🗺️Spatial Transcriptomics
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Gated DeltaNet (Linear Attention variant in Qwen3-Next and Kimi Linear)
⛰️Gradient Descent
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Multi-objective optimization of fuel electrode microstructure for cost-effective and high-performance solid oxide electrolysis cells
sciencedirect.com·20h
🗺️Spatial Transcriptomics
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The 5 FREE Must-Read Books for Every LLM Engineer
kdnuggets.com·1h
⛰️Gradient Descent
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HyFormer-Net: A Synergistic CNN-Transformer with Interpretable Multi-Scale Fusion for Breast Lesion Segmentation and Classification in Ultrasound Images
arxiv.org·1d
🗺️UMAP
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Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
arxiv.org·1d
🗺️UMAP
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A Dual-Use Framework for Clinical Gait Analysis: Attention-Based Sensor Optimization and Automated Dataset Auditing
arxiv.org·9h
📐Matrix Factorization
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Language-Enhanced Generative Modeling for PET Synthesis from MRI and Blood Biomarkers
arxiv.org·9h
🗺️UMAP
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MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
arxiv.org·1d
⛰️Gradient Descent
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Enhanced Fatigue Life Prediction in XLPE Power Cables via Multi-Modal Data Fusion & Bayesian Optimization
📊Empirical Bayes
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Uncertainty Quantification in Forward Problems: Balancing Accuracy and Robustness Using CWENO Interpolations
arxiv.org·1d
🎲Stochastic differential equation
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Spot The Ball: A Benchmark for Visual Social Inference
arxiv.org·1d
🗺️UMAP
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A Comparative Analysis of LLM Adaptation: SFT, LoRA, and ICL in Data-Scarce Scenarios
arxiv.org·1d
⛰️Gradient Descent
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Two-Parameter R\'enyi Information Quantities with Applications to Privacy Amplification and Soft Covering
arxiv.org·9h
📐Matrix Factorization
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Discriminately Treating Motion Components Evolves Joint Depth and Ego-Motion Learning
arxiv.org·1d
🗺️Manifold Learning
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