Shao-Qun Zhang

Orcid: 0000-0002-0614-8984

According to our database1, Shao-Qun Zhang authored at least 24 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Theoretical Exploration of Flexible Transmitter Model.
IEEE Trans. Neural Networks Learn. Syst., March, 2024

Neural Network Gaussian Processes by Increasing Depth.
IEEE Trans. Neural Networks Learn. Syst., February, 2024

On the Intrinsic Structures of Spiking Neural Networks.
J. Mach. Learn. Res., 2024

Horizon-wise Learning Paradigm Promotes Gene Splicing Identification.
CoRR, 2024

A Unified Kernel for Neural Network Learning.
CoRR, 2024

MEPSI: An MDL-Based Ensemble Pruning Approach with Structural Information.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Lax Extensions of Conical I-Semifilter Monads.
Axioms, November, 2023

On Discrete Presheaf Monads.
Axioms, June, 2023

Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Consistency Rate of Decision Tree Learning Algorithms.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Towards understanding theoretical advantages of complex-reaction networks.
Neural Networks, 2022

On the Approximation and Complexity of Deep Neural Networks to Invariant Functions.
CoRR, 2022

Structural Stability of Spiking Neural Networks.
CoRR, 2022

Theoretically Provable Spiking Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fault-Tolerant Energy-Efficient LoRaWAN Networking Architecture.
Proceedings of the 11th Mediterranean Conference on Embedded Computing, 2022

2021
Flexible Transmitter Network.
Neural Comput., 2021

Bifurcation Spiking Neural Network.
J. Mach. Learn. Res., 2021

ARISE: ApeRIodic SEmi-parametric Process for Efficient Markets without Periodogram and Gaussianity Assumptions.
CoRR, 2021

Towards Theoretical Understanding of Flexible Transmitter Networks via Approximation and Local Minima.
CoRR, 2021

Neural Network Gaussian Processes by Increasing Depth.
CoRR, 2021

Towards Understanding Theoretical Advantages of Complex-Reaction Networks.
CoRR, 2021

LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values.
Proceedings of the IEEE International Conference on Data Mining, 2021

2020
Harmonic Recurrent Process for Time Series Forecasting.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
Bifurcation Spiking Neural Network.
CoRR, 2019


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