QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities

Documenti analoghi

• Efficient Design of Compliant Mechanisms Using Multi-Objective Optimization
  di: Humer, Alexander, et al.
  Pubblicazione: (2025)
• Approximating Matrix Functions with Deep Neural Networks and Transformers
  di: Padmanabhan, Rahul, et al.
  Pubblicazione: (2026)
• Expressivity and Approximation Properties of Deep Neural Networks with ReLU$^k$ Activation
  di: He, Juncai, et al.
  Pubblicazione: (2023)
• SO-PIFRNN: Self-optimization physics-informed Fourier-features randomized neural network for solving partial differential equations
  di: Linghu, Jiale, et al.
  Pubblicazione: (2025)
• From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
  di: Wan, Ruyin, et al.
  Pubblicazione: (2025)