Category google-researches

google-researches

Multimodal Bottleneck Transformer (MBT): A New Model for Modality Fusion

Posted by Arsha Nagrani and Chen Sun, Research Scientists, Google Research, Perception Team People interact with the world through multiple sensory streams (e.g., we see objects, hear sounds, read words, feel textures and taste flavors), combining information and forming associations…

google-researches

Optimizing Airline Tail Assignments for Cleaner Skies

Posted by Emily Masten, Software Engineer, Google Research, Operations Research Team Airlines around the world are exploring several tactics to meet aggressive CO2 commitments set by the International Civil Aviation Organization (ICAO). This effort has been emphasized in Europe, where…

google-researches

Robust Graph Neural Networks

Posted by Bryan Perozzi, Research Scientist and Qi Zhu, Research Intern, Google Research Graph Neural Networks (GNNs) are powerful tools for leveraging graph-structured data in machine learning. Graphs are flexible data structures that can model many different kinds of relationships…

google-researches

Learning from Weakly-Labeled Videos via Sub-Concepts

Posted by Zizhao Zhang and Guanhang Wu, Software Engineers, Google Research, Cloud AI Team Video recognition is a core task in computer vision with applications from video content analysis to action recognition. However, training models for video recognition often requires…

google-researches

TRILLsson: Small, Universal Speech Representations for Paralinguistic Tasks

Posted by Joel Shor, Staff Software Engineer, Google Research In recent years, we have seen dramatic improvements on lexical tasks such as automatic speech recognition (ASR). However, machine systems still struggle to understand paralinguistic aspects — such as tone, emotion,…

google-researches

Using Deep Learning to Annotate the Protein Universe

Posted by Maxwell Bileschi, Staff Software Engineer and Lucy Colwell, Research Scientist, Google Research, Brain Team Proteins are essential molecules found in all living things. They play a central role in our bodies’ structure and function, and they are also…

google-researches

Co-training Transformer with Videos and Images Improves Action Recognition

Posted by Bowen Zhang, Student Researcher and Jiahui Yu, Senior Research Scientist, Google Research, Brain Team Action recognition has become a major focus area for the research community because many applications can benefit from improved modeling, such as video retrieval,…

google-researches

Federated Learning with Formal Differential Privacy Guarantees

Posted by Brendan McMahan and Abhradeep Thakurta, Research Scientists, Google Research In 2017, Google introduced federated learning (FL), an approach that enables mobile devices to collaboratively train machine learning (ML) models while keeping the raw training data on each user’s…

google-researches

Constrained Reweighting for Training Deep Neural Nets with Noisy Labels

Posted by Abhishek Kumar and Ehsan Amid, Research Scientists, Google Research, Brain Team Over the past several years, deep neural networks (DNNs) have been quite successful in driving impressive performance gains in several real-world applications, from image recognition to genomics.…

google-researches

4D-Net: Learning Multi-Modal Alignment for 3D and Image Inputs in Time

Posted by AJ Piergiovanni and Anelia Angelova, Research Scientists, Google Research While not immediately obvious, all of us experience the world in four dimensions (4D). For example, when walking or driving down the street we observe a stream of visual…