This paper takes a look at revisiting ResNets with improved training and regularization techniques.

This is the second paper by Google Brain using Semi-supervised learning for vision tasks.

A simple framework for a contrastive learning of visual representations.

This paper frames a general formulation of BERT into a Binary classification task so that a general model can be applied across domains with low and zero shot learning.

Magnetoresistive random-access memory (MRAM) devices are being researched to see their suitability to replace digital processors for machine learning workloads in orders of magnitudes lower power.

Every important division of machine learning, whether it be supervised learning, unsupervised learning, active learning, and reinforcement learning has been applied to Electronic Design Automation (EDA).

that is, minimum-Redundancy, Max-Dependency

I'm working on a project using MuZero architecture, and it references this paper as the basis of MuZero.

Let's dive into the images looking at ways to understand the Skip-Gram Model.

The first post on the Skip-Gram paper looks into understanding the abstract from the beginning and reviewing the images for clues.