Digital Twins: the missing pieces we can solve with Machine Learning
🗺️Manifold Learning
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Using Machine Learning in CAD to Detect Design Flaws Before They Become Costly
⛰️Gradient Descent
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A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques
nature.com·1d
🔥ComplexHeatmap
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A 10-meter resolution human footprint dataset to support biodiversity and conservation studies in Brazil
nature.com·6h
🔥ComplexHeatmap
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DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
arxiv.org·2d
🔲Zarr
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A Dual-Use Framework for Clinical Gait Analysis: Attention-Based Sensor Optimization and Automated Dataset Auditing
arxiv.org·1d
📐Matrix Factorization
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Automated Simulation Anomaly Detection via Multi-Modal Graph Analysis and Reinforcement Learning
🗺️Network Visualization
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What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later
towardsdatascience.com·2d
⛰️Gradient Descent
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Show HN: ReadMyMRI DICOM native preprocessor with multi model consensus/ML pipes
📄FASTQ
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ABIDES-MARL: A Multi-Agent Reinforcement Learning Environment for Endogenous Price Formation and Execution in a Limit Order Book
arxiv.org·1d
🗺️Network Visualization
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AI-Driven Predictive Hazard Mitigation via Dynamic Structural Health Monitoring
📊Empirical Bayes
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A Novel Reservoir Computing Framework for Chaotic Time Series Prediction Using Time Delay Embedding and Random Fourier Features
arxiv.org·15h
⛰️Gradient Descent
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<p>**Abstract:** This paper introduces a novel framework—Automated Semantic Validation & Anomaly Detection (ASVAD)—for rigorously evaluating and ensuring t...
freederia.com·1h
📄FASTQ
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A high-resolution large-scale dataset for building segmentation from aerial imagery in northeastern Italy
nature.com·3d
🔥ComplexHeatmap
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An Analysis of Early-Stage Functional Safety Analysis Methods and Their Integration into Model-Based Systems Engineering
arxiv.org·15h
📊Differential Expression
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Unlocking Logic's Secrets: BoolSkeleton – Streamlining Boolean Networks for Peak Performance by Arvind Sundararajan
⛰️Gradient Descent
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TA-LSDiff:Topology-Aware Diffusion Guided by a Level Set Energy for Pancreas Segmentation
arxiv.org·2d
🗺️UMAP
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