GitHub

Create a base class for sigmoid functions

We might consider having a base function for all sigmoid function, and add a class member that allows to control the vertical offset. We could then implement more models in addition to the Erf (or ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python Tropical Storm ...
IEEE

Sigmoid Function–Based Discontinuous Feedforward Current Ripple Modeling for Stability Analysis of Cascaded Converter

Abstract: The cascaded converter, under the switching ripple interaction between source and load converters, can be described as a high-order system with multiple switching state sequences (SSSs).
marktechpost

FlashSigmoid: A Hardware-Aware and Memory-Efficient Implementation of Sigmoid Attention Yielding a 17% Inference Kernel Speed-Up over FlashAttention-2 on H100 GPUs

Large Language Models (LLMs) have gained significant prominence in modern machine learning, largely due to the attention mechanism. This mechanism employs a sequence-to-sequence mapping to construct ...
IEEE

A Fully Probabilistic Model for Sigmoid Approximation and Its Hardware- Efficient Implementation

Abstract: The sigmoid function is a representative activation function in shallow neural networks. Its hardware realization is challenging due to the complex exponential and reciprocal operations.