Category google-researches

Deep Learning with Label Differential Privacy

Posted by Pasin Manurangsi and Chiyuan Zhang, Research Scientists, Google Research Over the last several years, there has been an increased focus on developing differential privacy (DP) machine learning (ML) algorithms. DP has been the basis of several practical deployments…

Vector-Quantized Image Modeling with Improved VQGAN

Posted by Jiahui Yu, Senior Research Scientist, and Jing Yu Koh, Research Software Engineer, Google Research In recent years, natural language processing models have dramatically improved their ability to learn general-purpose representations, which has resulted in significant performance gains for…

Contextual Rephrasing in Google Assistant

Posted by Aurelien Boffy, Senior Staff Software Engineer, and Roberto Pieraccini, Engineering Director, Google Assistant When people converse with one another, context and references play a critical role in driving their conversation more efficiently. For instance, if one asks the…

Learning Locomotion Skills Safely in the Real World

Posted by Jimmy (Tsung-Yen) Yang, Student Researcher, Robotics at Google The promise of deep reinforcement learning (RL) in solving complex, high-dimensional problems autonomously has attracted much interest in areas such as robotics, game playing, and self-driving cars. However, effectively training…

GraphWorld: Advances in Graph Benchmarking

John Palowitch and Anton Tsitsulin, Research Scientists, Google Research, Graph Mining team Graphs are very common representations of natural systems that have connected relational components, such as social networks, traffic infrastructure, molecules, and the internet. Graph neural networks (GNNs) are…