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Heiko Hoffmann gives an overview of the “Neural Descriptor Fields” paper. He first goes over how the Neural Descriptor Fields (NDFs) function represents key points on a 3D object relative to its position and pose, and how NDFs can be used to recover an object’s position and pose. He then discusses the paper’s simulation and robot-experiment results and highlights the useful concepts and limits of the paper. In the second half of the meeting, Karan Grewal presents the “Vector Neurons” paper. He first gives a quick review of the core concepts and terminology of the paper. Then he looks into the structure of the paper’s SO(3)-equivariant neural networks in detail and how the networks represent object pose and rotation. Lastly, Karan goes over the results of object classification and image reconstruction and points out a few shortcomings. “Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation” by Anthony Simeonov et al.: https://arxiv.org/abs/2112.05124 “Vector Neurons: A General Framework for SO(3)-Equivariant Networks” by Congyue Deng et al. https://arxiv.org/abs/2104.12229 Datasets mentioned: Shapenet: https://shapenet.org/taxonomy-viewer ModelNet40: https://3dshapenets.cs.princeton.edu/ - - - - 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/