In the new paper Canonical Capsules: Unsupervised Capsules in Canonical Pose, Turing Award Honoree Dr. Geoffrey Hinton and a team of researchers propose an architecture for unsupervised learning with 3D point clouds based on capsules.
This year, 22 Transformer-related research papers were accepted by NeurIPS, the world’s most prestigious machine learning conference. Synced has selected ten of these works to showcase the latest Transformer trends.
This year, NeurIPS is hosting two workshops dedicated to self-supervised learning: Self-Supervised Learning for Speech and Audio Processing on Friday, December 11; and Self-Supervised Learning — Theory and Practice on Saturday, December 12.
OpenAI’s groundbreaking GPT-3 language model paper, a no-regret learning dynamics study from Politecnico di Milano & Carnegie Mellon University, and a UC Berkeley work on data summarization have been named the NeurIPS 2020 Best Paper Award winners.
The approach dramatically reduces bandwidth requirements by sending only a keypoint representation [of faces] and reconstructing the source video on the receiver side with the help of generative adversarial networks (GANs) to synthesize the talking heads.
Google’s UK-based lab and research company DeepMind says its AlphaFold AI system has solved the protein folding problem, a grand challenge that has vexed the biology research community for half a century.