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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 ...
GitHub

Using numpy on AWS Lambda Functions

I don't know if the right place to write this, but it a help for someone is working with AWS Lambda Function and is facing problem on to import the numpy. numpy is not available by default on the AWS ...
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.