Neural network, Backpropagation, Information retrieval, Plinko, Determinant, Equivalence relation
Click here to read the article
3 Deep Symmetry Networks Deep symmetry networks represent rich compositional structure that incorporates invariance to high- dimensional symmetries. S(M [l − 1, Il−1])(P′) 〉 (3) 3 Layer l Feature map i Layer l-1 Feature maps 0,1,2 Layer l-1 Pooled feature maps 0,1,2 Kernels Figure 1: The ...
Click here to read the article
3 Deep Symmetry Networks Deep symmetry networks represent rich compositional structure that incorporates invariance to high- dimensional symmetries. S(M [l − 1, Il−1])(P′) 〉 (3) 3 Layer l ...
We are sorry, we could not find the related article
If you are curious about Artificial Intelligence News Essentials and General News
Please click on:
Or signup to our newsletters
Artificial Intelligence and Deep Learning For the Extremely Confused
The watershed moment in Deep Learning is typically cited as 2012’s AlexNet, by Alex Krizhevsky and Geoffrey Hinton, a state of the art GPU accelerated Deep Learning network that won that ...
Demystifying Convolutional Neural Networks
An Intuitive Explanation of Convolutional Neural Networks.
Click here to read the article
Specifically, we do language modeling in both the forward and backward directions to pretrain the weights of NER 2 Bidirectional Language Modeling for Transfer Learning in Biomedical NER ...
Flow-based Deep Generative Models
In this post, we are looking into the third type of generative models: flow-based generative models. Different from GAN and VAE, they explicitly learn the pr...
Are capsules a good idea? A generative perspective
I’ve recently written a paper on a fully probabilistic version of capsule networks. While trying to get this kind of model to work, I found some interesting conceptual issues with the ideas ...