david silver google scholar

The ones marked * may be different from the article in the profile. Try again later.The following articles are merged in Scholar. Their papers tend to amass citations much faster than papers in influential journals such as Such rapid accumulation of citations may be in part explained by the fact that at these annual conferences that can attract thousands of attendees from around the world, new software, which is often open source, is shared and later built upon by the community.Below is our 2020 selection of Google Scholar’s most highly-cited articles published by the world's most influential journals.Adam is a popular optimization algorithm for deep learning – a subset of machine learning that uses artificial neural networks inspired by the human brain to imitate how the brain develops certain types of knowledge.Adam was introduced in this paper at the 2014 International Conference on Learning Representations (ICLR) by Diederik P. Kingma, today a machine learning researcher at Google, and Jimmy Ba from the Machine Learning Group at the University of Toronto, Canada. David Silver, Julian Schrittwieser and Karen Simonyan: These authors contributed equally to this work. Affiliations. DeepMind, 5 New Street Square, London, EC4A 3TW, UK Merged citations. Artificial intelligence (AI) research Computer vision research in particular attracts a high number of citations over a short period of time. DAVID SILVER. That paper, presented at the 2015 IEEE International Conference on Computer Vision in Chile, has amassed It centres on reinforcement learning – how machine learning models are trained to make a series of decisions by interacting with their environments.The paper was authored by a team from Google DeepMind, a London-based organization acquired by Google in 2014 that has developed AI technologies for the diagnosis of eye diseases, energy conservation, and to predict the complex 3D structures of proteins.Authored by researchers at Google Brain and Google Research, this paper proposed a new deep learning model called the Transformer.Designed to process sequential data such as natural language, Transformer is used by translation, text summarization, and voice recognition technologies, and other applications that use sequence analysis such as DNA, RNA, and peptide sequencing. David Silver (born c. 1976) leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo, AlphaZero and co-lead on AlphaStar.. That paper was co-authored by Ross Girshick, one of the invertors of R-CNN and now a research scientist at Facebook AI.In the same week that "Faster R-CNN" was presented by Ren and his colleagues, Girshick presented a paper on "Fast R-CNN", another version of R-CNN, at a different conference. Their combined citations are counted only for the first article. Le décompte "Citée par" inclut les citations des articles suivants dans Google Scholar. Citations en double. In May 2020, the conference drew 5,600 participants from nearly 90 countries to its virtual sessions – Presented at the 2015 Neural Information Processing Systems annual meeting in Canada, this paper describes what has now become the most widely used version of an object detection algorithm called Object detection is a major part of computer vision research, used to identify objects such as humans, cars, and buildings in images and videos.The lead author, Shaoqing Ren, is also a co-author on Google’s most-cited paper for 2020, "Deep Residual Learning for Image Recognition", which has amassed almost 50,000 citations. Importer un PDF. David Silver (R) is one of the researchers who developed AlphaGo.Google Scholar has released its annual ranking of most highly-cited publications. Peer Pressure and Productivity in the Emergency Department" R&R, Review of Economic … Email: david.silver@princeton.edu: Address: Department of Economics Princeton University 124 Julis Romo Rabinowitz Building Princeton, NJ 08544: I am an Assistant Professor of Economics and Public Affairs at Princeton University.

Many of the most highly-cited papers in this ranking are centred on object detection and image recognition – research that is crucial for technologies such as self-driving cars and surveillance.The high citations numbers for AI-related papers confirm it as a "hot" research field, as is also evidenced by the increasing importance placed on it by governments.In April, the European Commission announced that it is Google Scholar is the largest database in the world of its kind, tracking citation information for almost 400 million academic papers and other scholarly literature.The most highly-cited paper of all, "Deep Residual Learning for Image Recognition", published in “Deep learning”, a seminal review of the potential of AI technologies that was published in Though it is common practice, assessing research quality based on narrow metrics such as citations or journal of publication is increasingly controversial in the research community.

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