Neural
Artificial Intelligence
The Best Optimization Algorithm for Your Neural Network
Learn how to select it and minimize your neural network training time.The above cycle is repeated multiple times until satisfactory performance levels are achieved. The “experiment” phase involves each the coding and the training...
Artificial Intelligence
Discovering Differential Equations with Physics-Informed Neural Networks and Symbolic Regression
A case study with step-by-step code implementation25 min read·11 hours agoSuch partial knowledge of the governing differential equations hinders our understanding and control of those dynamical systems. Consequently, inferring these unknown components based on...
Artificial Intelligence
Recurrent Neural Networks, Explained and Visualized from the Ground Up Complex Flavors of Recurrent Networks Neural Machine Translation Text-Output Recurrent Models Bidirectionality Autoregressive Generation 2016 Google Translate
The design of the Recurrent Neural Network (1985) is premised upon two observations about how a great model, similar to a human reading text, would process sequential information:It should track the data ‘learned’ up...
Artificial Intelligence
A Easy Conceptual Overview of Neural Network and Deep Learning
Now we've gained some basic understanding of what a neural network is, the way it functions, and what hyperparameters are involved in tunning, we will bring up the concept of deep learning.So, what exactly...
Artificial Intelligence
My Journey with Machine Learning Algorithms Embarking on the Machine Learning Adventure What are Machine Learning Algorithms? Varieties of Machine Learning Algorithms 1. Supervised Learning: Guiding Computers with...
Hold on tight, because Huy is back with a bang, able to captivate you with the wonders of machine learning!I'm excited to accompany you on a rare voyage into the charming universe of machine...
Artificial Intelligence
Direction Improves Graph Learning Measuring Homophily in Directed Graphs A Toy Example Dir-GNN: Directed Graph Neural Network Experimental Results
Many interesting real-world graphs, encountered in modelling social, transportation, financial transactions, or academic citation networks, are directed. The direction of the perimeters often conveys crucial insights, otherwise lost if one considers only the connectivity...
Artificial Intelligence
Empowering Efficient BO Transfer with Neural Acquisition Process (NAP) General Objectives & Results: From Bayesian Optimisation to Meta-Bayesian Optimisation: Neural Acquisition Processes (NAP): Cool Properties:
Our primary objective is to reinforce the effectiveness of Bayesian Optimisation (BO) by leveraging meta-learning to transfer knowledge across different problem domains, thereby significantly improving sample efficiency.In pursuit of this goal, we introduce the...
Artificial Intelligence
Empowering Efficient BO Transfer with Neural Acquisition Process (NAP) General Objectives & Results: From Bayesian Optimisation to Meta-Bayesian Optimisation: Neural Acquisition Processes (NAP): Cool Properties:
Our primary objective is to boost the effectiveness of Bayesian Optimisation (BO) by leveraging meta-learning to transfer knowledge across different problem domains, thereby significantly improving sample efficiency.In pursuit of this goal, we introduce the...
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