The Connectivity, Information & Intelligence Lab (Ci2Lab), directed by Professor Reza Arghandeh, has a simple goal: explain infrastructure networks with data analytics. Our research focuses on the intersection of machine learning, causal inference, and complex networks. We endeavor to answer how infrastructure networks are interconnected, how the environment impacts them (and the other way around), and how they shape our lives.
💡 Learn more on our official website.
This course is an overview of applied causal inference.
Forked from MicheleGazzea/Sar_opt_matching
Code for MARU-Net: Multi-Scale Attention Gated Residual U-Net With Contrastive Loss for SAR-Optical Image Matching, published in https://ieeexplore.ieee.org/abstract/document/10129005
Python 1
Code for the LarynxFormer framework.
Python 1
Code for MARU-Net: Multi-Scale Attention Gated Residual U-Net With Contrastive Loss for SAR-Optical Image Matching, published in https://ieeexplore.ieee.org/abstract/document/10129005
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