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1. Hyper-Compression: Model Compression via Hyperfunction

2. Don't Fear Peculiar Activation Functions: EUAF and Beyond

3. Structured and Balanced Multi-component and Multi-layer Neural Networks

5. Tracking dynamic flow: Decoding flow fluctuations through performance in a fine motor control task

6. Deep Network Approximation: Beyond ReLU to Diverse Activation Functions

7. Why Shallow Networks Struggle with Approximating and Learning High Frequency: A Numerical Study

9. On Enhancing Expressive Power via Compositions of Single Fixed-Size ReLU Network

10. Study on the Influence of Wildfire on Streamer Discharge in Transmission Line Gap

11. Neural Network Architecture Beyond Width and Depth

17. Deep Network Approximation in Terms of Intrinsic Parameters

21. Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons

26. Optimal Approximation Rate of ReLU Networks in terms of Width and Depth

33. Neural Network Approximation: Three Hidden Layers Are Enough

34. Deep Network with Approximation Error Being Reciprocal of Width to Power of Square Root of Depth

35. Deep Network Approximation for Smooth Functions

38. Deep Network Approximation Characterized by Number of Neurons

39. Nonlinear Approximation via Compositions

46. Research on Early Warning and Disposal Technology of Intelligent IoT Terminal Security Threat

47. Research on Identification Method of Sensitive Data in Power System

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