Doctor AI
hen faced with medical issues, would you want to be seen by a human or a machine? In this episode, guest Edward Choi, co-author of the study titled Doctor AI: Predicting Clinical Events via Recurrent ...
23 Kesä 201741min
[MINI] Activation Functions
In a neural network, the output value of a neuron is almost always transformed in some way using a function. A trivial choice would be a linear transformation which can only scale the data. However, o...
16 Kesä 201714min
MS Build 2017
This episode recaps the Microsoft Build Conference. Kyle recently attended and shares some thoughts on cloud, databases, cognitive services, and artificial intelligence. The episode includes intervi...
9 Kesä 201727min
[MINI] Max-pooling
Max-pooling is a procedure in a neural network which has several benefits. It performs dimensionality reduction by taking a collection of neurons and reducing them to a single value for future layers ...
2 Kesä 201712min
Unsupervised Depth Perception
This episode is an interview with Tinghui Zhou. In the recent paper "Unsupervised Learning of Depth and Ego-motion from Video", Tinghui and collaborators propose a deep learning architecture which is...
26 Touko 201723min
[MINI] Convolutional Neural Networks
CNNs are characterized by their use of a group of neurons typically referred to as a filter or kernel. In image recognition, this kernel is repeated over the entire image. In this way, CNNs may achi...
19 Touko 201714min
Multi-Agent Diverse Generative Adversarial Networks
Despite the success of GANs in imaging, one of its major drawbacks is the problem of 'mode collapse,' where the generator learns to produce samples with extremely low variety. To address this issue, t...
12 Touko 201729min
[MINI] Generative Adversarial Networks
GANs are an unsupervised learning method involving two neural networks iteratively competing. The discriminator is a typical learning system. It attempts to develop the ability to recognize members of...
5 Touko 20179min
