Zenan Ling
Orcid: 0000-0001-8047-0253
According to our database1,
Zenan Ling
authored at least 22 papers
between 2016 and 2024.
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Bibliography
2024
Deep Equilibrium Models are Almost Equivalent to Not-so-deep Explicit Models for High-dimensional Gaussian Mixtures.
CoRR, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Optimization Induced Equilibrium Networks: An Explicit Optimization Perspective for Understanding Equilibrium Models.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2023
On the Equivalence between Implicit and Explicit Neural Networks: A High-dimensional Viewpoint.
CoRR, 2023
CoRR, 2023
Codebook Configuration for 1-bit RIS-aided Systems Based on Implicit Neural Representations.
CoRR, 2023
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Joint Conference on Neural Networks, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Brown Measure Based Spectral Distribution Analysis for Spatial-Temporal Localization of Cascading Events in Power Grids.
IEEE Trans. Smart Grid, 2021
A New Approach of Exploiting Self-Adjoint Matrix Polynomials of Large Random Matrices for Anomaly Detection and Fault Location.
IEEE Trans. Big Data, 2021
2020
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks.
IEEE Trans. Smart Grid, 2020
2019
IEEE Access, 2019
2018
Massive Streaming PMU Data Modelling and Analytics in Smart Grid State Evaluation based on Multiple High-Dimensional Covariance Test.
IEEE Trans. Big Data, 2018
CoRR, 2018
An Accurate and Real-time Self-blast Glass Insulator Location Method Based On Faster R-CNN and U-net with Aerial Images.
CoRR, 2018
A Novel Data-Driven Situation Awareness Approach for Future Grids - Using Large Random Matrices for Big Data Modeling.
IEEE Access, 2018
2017
Individual Recognition in Schizophrenia using Deep Learning Methods with Random Forest and Voting Classifiers: Insights from Resting State EEG Streams.
CoRR, 2017
2016
Designing for Situation Awareness of Future Power Grids: An Indicator System Based on Linear Eigenvalue Statistics of Large Random Matrices.
IEEE Access, 2016