Summary of A Physics-driven Sensor Placement Optimization Methodology For Temperature Field Reconstruction, by Xu Liu et al.
A physics-driven sensor placement optimization methodology for temperature field reconstructionby Xu Liu, Wen Yao, Wei…
A physics-driven sensor placement optimization methodology for temperature field reconstructionby Xu Liu, Wen Yao, Wei…
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Weather Prediction Using CNN-LSTM for Time Series Analysis: A Case Study on Delhi Temperature Databy…
Leveraging Large Language Models for Solving Rare MIP Challengesby Teng Wang, Wing-Yin Yu, Ruifeng She,…
ForeCal: Random Forest-based Calibration for DNNsby Dhruv NigamFirst submitted to arxiv on: 4 Sep 2024CategoriesMain:…
From Data to Insights: A Covariate Analysis of the IARPA BRIAR Dataset for Multimodal Biometric…
Correlating Time Series with Interpretable Convolutional Kernelsby Xinyu Chen, HanQin Cai, Fuqiang Liu, Jinhua ZhaoFirst…