Blog Topics Advertise Join Newsletter Bayesian Networks (6) --> DeepMind Relies on this Old Statistical Method to Build Fair Machine Learning Models - Oct 23, 2020. Causal Bayesian Networks are used to model the influence of fairness attributes in a dataset. DeepMind is Using This Old Technique to Evaluate Fairness in Machine Learning Models - Oct 28, 2019. Visualizing the datasets is an essential component to identify potential sources of bias and unfairness. DeepMind relied on a method called Causal Bayes
Abstract page for arXiv paper 2202.07679: Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks
ReLU, short for Rectified Linear Unit, is an activation function that outputs the input if it is positive and zero otherwise. Its formula is f(x) = max(0, x).
A biphasic structural plasticity rule interacts with homeostatic synaptic scaling to maintain firing rate homeostasis in neural networks
go wash your hands THE BEGINNING OF TIME Pokemon generated by neural network lewisandquark : I’ve been playing around with char-rnn, an open-source torch add-on for character-based neural networks by Andrej Karpathy , using it to generate everything from cookbook recipes to superhero names to a Lovecraft/cookbook mashup . I decided to train the neural network to randomly generate Pokemon names and abilities based on this list as a training set - and found that it was good at generating Pokemon. Annoyingly
This paper proposes k-dimensional graph neural networks that surpass 1-WL limits using hierarchical architectures for capturing higher-order graph features
An elementary finite-time account of why wide networks trained on the same minibatches develop matching local loss fluctuations, and how width and batch size control initialization, data, and interaction noise, with implications on scaling
# Explainer: How neural networks are changing credit scores By Digiday • February 27, 2017 • A credit score has a major impact on a person’s life. It’s the key to getting a car loan, a house or an apartment. The traditional way scores are calculated is a method called logistic regression, which means assigning a value to a number of factors in your financial life (for example, payment history, number of credit accounts, length of credit history) and weighing them. But credit bureaus are now looking
Neural Networks (NNs) are used in various application areas to identify objects. Reliable behavior of NNs is an important aspect, especially for embedded systems. In this paper, we focus on the analysis of NNs to find correlations between their characteristics in
The goal of this assignment is to explore regularization techniques.