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RESEARCH PAPER · Electronics · 2022

Theory-Guided Deep Learning Algorithms: An Experimental Evaluation

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10 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Theory-Guided Deep Learning Algorithms: An Experimental EvaluationOriginalHow Does Knowledge Injection Help in Informed Machine Learning?3A General Model for Side Information in Neural Networks1A Neural Network with Physical Mechanism for Predicting Airport Aviation Noise12Theory-Guided Data-Science for Battery Modeling: Insights from a Comparative Study0A comparative study of neural ordinary differential equations and neural operators for modeling temporal dynamics1Adversarial Robustness0Enforcing domain constraints through Lagrangian primal-dual learning0Toward Knowledge-Enhanced Geohazard Intelligence: A Review of Knowledge Graphs and Large Language Models1A physics-guided explainable machine learning framework for residual-based performance deviation detection and probabilistic severity assessment in photovoltaic systems4Theory-guided AI for scalable random access in massive machine-type communications0

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  1. How Does Knowledge Injection Help in Informed Machine Learning?

    Unknown journal · 2023-06-18

    Laura von Rueden, Jochen Garcke, Christian Bauckhage

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  2. A General Model for Side Information in Neural Networks

    Algorithms · 2023-11-15

    Tameem Adel, Mark Levene

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  3. A Neural Network with Physical Mechanism for Predicting Airport Aviation Noise

    Aerospace · 2024-09-12

    Dan Yang Zhu, Jiayu Peng, Cong Ding

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  4. Theory-Guided Data-Science for Battery Modeling: Insights from a Comparative Study

    IEEE International Conference on Data Science and Advanced Analytics (DSAA) · 2024-10-06

    Pawel Bielski, Nico Denner, Simon Bischof, Benedikt Rzepka, Klemens Böhm

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  5. A comparative study of neural ordinary differential equations and neural operators for modeling temporal dynamics

    Neural Computing and Applications · 2025-09-09

    Matteo Celia, Simone Monaco, Daniele Apiletti

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  6. Adversarial Robustness

    International Conference on Advances in Artificial Intelligence (ICAAI) · 2025-11-14

    Tameem Adel

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  7. Enforcing domain constraints through Lagrangian primal-dual learning

    Neural Computing and Applications · 2026-03-21

    Simone Monaco, Flavio Giobergia, Alkis Koudounas, Daniele Apiletti

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  8. Toward Knowledge-Enhanced Geohazard Intelligence: A Review of Knowledge Graphs and Large Language Models

    GeoHazards · 2026-04-07

    W. H. Li, Yongzhang Zhou

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  9. A physics-guided explainable machine learning framework for residual-based performance deviation detection and probabilistic severity assessment in photovoltaic systems

    Clean Energy · 2026-05-27

    Roby Mohajon, Shuva Chandra Sarker, Md Amzad Sadik Abid, Simanta Datta Ronobir, Abid Kamal Rumi, Shimul Chakraborty, Adiba Juoairia, Nur Mohammad

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  10. Theory-guided AI for scalable random access in massive machine-type communications

    International Journal of Machine Learning and Cybernetics · 2026-09-17

    Zongxiao Li, Lin Wei, Jun-Ting Liu, Jun-Ting Liu, Ngo Van Mao, Binbin Chen, Jianwei Liu, Jianwei Liu

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