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This is part 2 of the Activation Function Series. In this video, we will discuss the dying relu problem and then learn about the ...

In artificial neural networks, each neuron forms a weighted sum of its inputs and passes the resulting scalar value through a ...

Welcome to Lecture 27 of Machine Learning: Teach by Doing project. In this lecture, we learn all about activation functions.

This video is the continuation of the activation functions from my complete deep learning playlist.In this video we will cover the ...

This is the fourth video in the series of talks on Computer Vision Talks! Here We Discussed the paper- " Mish-A Self Regularized ...

Deep Learning & Neural Networks are behind the vast majority of the Artificial Intelligence that is sweeping the world. In Part 3, we ...

Unlock the power of the ReLU (Rectified Linear Unit) activation function in deep learning. In this video, I break down everything ...

Zoom meeting with our special guest from RELU. We will be including the option to upload AI segmentations.

Carnegie Mellon University Course: 11-785, Intro to Deep Learning Offering: Spring 2019 Slides: ...

This workshop - organised under the auspices of the Isaac Newton Institute on “Approximation, sampling and compression in data ...

Applications of neural networks are rapidly transforming numerous fields, yet a rigorous mathematical foundation for their ...

Sitan Chen (MIT) https://simons.berkeley.edu/talks/learning-deep-relu-networks-fixed-parameter-tractable Learning and Testing in ...

Abstract: The parameter space for any fixed architecture of neural networks serves as a proxy during training for the associated ...

https://github.com/zekelabs/tensorflow-tutorial.

In this part, we will see how to calculate Gradients for a single Neuron when ReLu activation is used. The Loss function is Mean ...

A video about neural networks, function approximation, machine learning, and mathematical building blocks. Dennis Nedry did ...

A growing body of research illustrates that neural network generalization performance is less dependent on the network size (i.e. ...

Deep Neural Networks Video 11 - ReLU Activation.

This paper studies the problem of range analysis for feedforward neural networks, which is a basic primitive for applications such ...

Speakers, institutes & titles 1. Kamaljyoti Nath, Brown University, A Dimension-Augmented Physics-Informed Neural Network ...