Jonathan Weed
About
Jonathan Weed has authored 12 papers that have received a total of 263 indexed citations.
This includes 3 papers in Artificial Intelligence, 3 papers in Statistics and Probability and 3 papers in Numerical Analysis. The topics of these papers are Advanced Optimization Algorithms Research (3 papers), Markov Chains and Monte Carlo Methods (2 papers) and Statistical Methods and Inference (2 papers). Jonathan Weed is often cited by papers focused on Advanced Optimization Algorithms Research (3 papers), Markov Chains and Monte Carlo Methods (2 papers) and Statistical Methods and Inference (2 papers) and collaborates with scholars based in United States, United Kingdom and France. Jonathan Weed's co-authors include Philippe Rigollet, Afonso S. Bandeira, Amit Singer, Ziv Goldfeld and Jason M. Altschuler and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Information Theory and Journal of Machine Learning Research
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