Energy-Based Modeling defines probabilistic systems using an energy function that assigns lower values to more likely configurations. Such models are used in machine learning for pattern recognition, density estimation, and structured prediction. By learning an energy landscape, they capture dependencies among variables without explicit normalization. Energy-based approaches have applications in vision, natural language, and physics-inspired computation. They provide a flexible framework for modeling complex data distributions.
Distributed fiber-optic sensing combined with machine learning enables continuous monitoring of telecom infrastructure. We employ generative modeling for event classification, supporting semi supervised learning, uncertainty calibration, and noise resilience. Our approach offers a scalable, data-efficient solution for real-world deployment in complex environments.
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NEC Laboratories America, Inc. (NEC Labs) is the US-based center for NEC Corporation’s global network of corporate research laboratories. Our diverse research groups collaborate with industry, academia and governments to provide disruptive solutions to complex problems. A leader in the integration of IT and network technologies with more than 100 years of expertise, NEC provides a combination of products and solutions that cross-utilize the company’s experience and global resources to meet the complex and ever-changing needs of its customers.