/explore

Click through on any links that interest you or select the planets on the right to continue exploring the Outer Web.
You are here

 sander.ai
Slides for my talk at the Deep Learning London meetup - Sander Dieleman
| | ajolicoeur.ca
Fashion repeats itself: Generating tabular data via Diffusion and XGBoost - Alexia Jolicoeur-Martineau, Ph.D.
2.2 parsecs away

Travel
| | Paper / Code Since AlexNet showed the world the power of deep learning, the field of AI has rapidly switched to almost exclusively focus on deep learning. Some of the main justifications are that 1) neural networks are Universal Function Approximation (UFA, not UFO ?), 2) deep learning generally works the best, and 3) it...
| | studywolf.wordpress.com
Spiking neural networks take control | studywolf
1.6 parsecs away

Travel
| | Back in September I had an review article in Science Robotics published, discussing new work from Abadia et al, 2021 titled A cerebellar-based solution to the nondeterministic time delay problem in robotic control. In my review I talk about the parallel's between the brain inspired approach Abadia et al used to create a neural circuit...
| | polukhin.tech
Lightweight Neural Network Architectures | Andrii Polukhin
1.2 parsecs away

Travel
| | As the field of Deep Learning continues to grow, the demand for efficient and lightweight neural networks becomes increasingly important. In this blog post, we will explore six lightweight neural network architectures.
| | comsci.blog
Step-by-Step Guide to Image Classification with Vision Transformers (ViT) | ML and robotics notes
17.7 parsecs away

Travel
| In this blog post, we will learn about vision transformers (ViT), and implement an MNIST classifier with it. We will go step-by-step and understand every part of the vision transformers clearly, and you will see the motivations of the authors of the original paper in some of the parts of the architecture.