Machine Learning

Gumbel Softmax (a.k.a. Concrete distribution)

While it might still be too early to start talking about the next A.I. winter, researchers are starting to see the limits of machine learning’s current set of…

(PPS) DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

This paper deals with semantic segmentation: the task of labeling pixels in an image by their object classes. The goal of semantic…

(PPS) Efficient Deep Learning for Stereo Matching

(PPS) Dynamic Routing Between Capsules

Capsules is one of the recent works coming from Geoff Hinton which is why it’s so hyped up…

(PPS) Deformable Convolutional Networks

The basic idea of this paper is to give the convolution and pooling layers the ability to model different orientations and scales of objects in images. They do this by making the shape of the convolution filter learnable. For intuition, consider the…