We’re proud to work with academic and research institutions to push the boundaries of AI and computer science. I’m an AI resident at Google Brain in Zurich, conducting research in transfer learning. Brain Research Institute, Laboratory of Neural Connectivity, University of Zurich foldy@hifo.uzh.ch. We solve big challenges in computer science, with a focus on machine learning, natural language understanding, machine perception, algorithms and data compression. TensorFlow Hub is a platform to publish, discover, and reuse parts of machine learning modules in TensorFlow. Florian Wenzel is a postdoctoral researcher at Google Brain Berlin working in the field of Bayesian deep learning. In 2018, we added support for handwriting recognition in more than 100 languages to Gboard for Android, Google's keyboard for mobile devices. Scale peak hardware and software challenges at our Europe engineering hub in Zurich, where we push technology forward while making great local and … The team focuses on advancing the application of machine intelligence through consultancy, state-of-the-art infrastructure development and education. Petra Ehmann Augmented Reality @Google - BILANZ Top 100 Digital Shaper - Stanford and ETH Alumna Zürich, Schweiz. I really enjoy working with colleagues who have a broad range of expertise on cutting-edge machine learning research problems that have the potential of improving the lives of billions of people. I blog about machine learning (ML) and how to learn ML at jessicayung.com. Martin Jaggi EPFL Verified email at epfl.ch. Their combined citations are counted only for the first article. AI researcher @ Google Brain working on Natural Language Understanding. Our teams in Zürich have concentrations in theoretical and application aspects of computer science with a strong focus on machine learning—from algorithmic foundations and theoretical underpinnings of deep learning to natural language understanding and machine perception. Subarachnoid hemorrhage is a stroke subtype with particularly bad outcome. Our broad and fundamental research goals allow us to actively collaborate with, and contribute uniquely to, many other teams across Alphabet who deploy our cutting edge technology into products. However, the nature of the detailed neurobiological... Niru Maheswaranathan, Alex Williams, Matthew Golub, Surya Ganguli, David Sussillo. Improve people’s lives. At Google AI, we’re conducting research that advances the state-of-the-art in the field, applying AI to products and to new domains, and developing tools to ensure that everyone can access AI. Go behind the scenes and meet some of the people on the Google Brain team who are helping shape machine learning itself. End to end Handwriting Recognition in Gboard In 2018, we added support for handwriting recognition in more than 100 languages to Gboard for Android, Google's keyboard for mobile devices. Deep Learning Researcher - Lead Google Brain Zurich Zürich, Schweiz. By being incredibly innovative, flexible and tailored for the particular needs and culture of the company and its employees, Google’s EMEA Engineering Hub in Zurich, Switzerland, is a great example of a modern workspace design, which cultivates an energized and inspiring work environment that is relaxed but focused, and buzzing with activities. Most of the Brain team is based in Mountain View, but we have smaller groups of team members in Cambridge (Massachusetts), London, Montreal, New York, San Francisco, Toronto and Zurich. degree (cum laude) in Computer Science from Politecnico di Milano (Italy), and a B.Sc. Meet a few of our machine learning makers, Reducing the variance in online optimization by transporting past gradients, Private Stochastic Convex Optimization with Optimal Rates, Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes, Universality and Individuality in recurrent networks, Differentiable Ranking and Sorting using Optimal Transport, Advances in Neural Information Processing Systems (NeurIPS) 32, DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections, Private Learning Implies Online Learning: An Efficient Reduction. We believe that openly disseminating research is critical to a healthy exchange of ideas, leading to rapid progress in the field. Our researchers publish regularly in academic journals, release projects as open source, and apply research to Google products. 13 Connections There was a problem loading your content. marcvanzee.nl. 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