Browsing: Yannic Kilcher
I retrace my first reading of Facebook AI’s DETR paper and explain my process of understanding it. OUTLINE: 0:00 -…
Neural networks are very good at predicting systems’ numerical outputs, but not very good at deriving the discrete symbolic equations…
In this part, we go over the formal definition of the measure of intelligence. In order to do this, we…
Backpropagation is one of the central components of modern deep learning. However, it’s not biologically plausible, which limits the applicability…
Object detection often does not occur in a vacuum. Static cameras, such as wildlife traps, collect lots of irregularly sampled…
We’ve become very good at making generative models for images and classes of images, but not yet of sets of…
Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the nature…
Google builds a 600 billion parameter transformer to do massively multilingual, massive machine translation. Interestingly, the larger model scale does…
Proteins are the workhorses of almost all cellular functions and a core component of life. But despite their versatility, all…
In this part, we look at the ARC challenge as a proposed test of machine intelligence. The dataset features 1000…