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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Detailed Technical Documentation on AI Implementation Logic (Taking Large Language Models as an Example )
🔢Embeddings
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A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques
nature.com·22h
🔥ComplexHeatmap
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LDBT instead of DBTL: combining machine learning and rapid cell-free testing
nature.com·22h
🧬Genomics
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TabGemma: Text-Based Tabular ICL via LLM using Continued Pretraining and Retrieval
arxiv.org·8h
🔢Embeddings
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MammoClean: Toward Reproducible and Bias-Aware AI in Mammography through Dataset Harmonization
arxiv.org·1d
📦Pseudobulk
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Imprecise model of thunderstorm wind speed and uncertainty propagation on the maximum dynamic response
sciencedirect.com·21h
🔗Markov Chains
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flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R
arxiv.org·2d
📄FASTQ
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What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later
towardsdatascience.com·1d
⛰️Gradient Descent
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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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