"Learning Physical Graph Representations from Visual Scenes" Paper Review - December 22, 2021

Описание к видео "Learning Physical Graph Representations from Visual Scenes" Paper Review - December 22, 2021

Numenta Research Intern Abhiram Iyer presents the paper “Learning Physical Graph Representations from Visual Scenes” by D. Bear et al.

He first gives some context and an overview of physical scene graphs. He then explains the pipeline of how these graphs are built in the deep learning system, starting with 1. feature extraction 2. graph pooling 3. graph vectorization, and 4. graph construction. Lastly, he goes through the results from the paper, the caveats, and his main takeaways.

Paper: https://proceedings.neurips.cc/paper/...
- - - -
Numenta is leading the new era of machine intelligence. Our deep experience in theoretical neuroscience research has led to tremendous discoveries on how the brain works. We have developed a framework called the Thousand Brains Theory of Intelligence that will be fundamental to advancing the state of artificial intelligence and machine learning. By applying this theory to existing deep learning systems, we are addressing today’s bottlenecks while enabling tomorrow’s applications.

Subscribe to our News Digest for the latest news about neuroscience and artificial intelligence:
https://numenta.com/news-digest/

Subscribe to our Newsletter for the latest Numenta updates:
https://tinyurl.com/NumentaNewsletter

Our Social Media:
  / numenta  
  / officialnumenta  
  / numenta  

Our Open Source Resources:
https://github.com/numenta
https://discourse.numenta.org/

Our Website:
https://numenta.com/

Комментарии

Информация по комментариям в разработке