Radford M. Neal
Radford M. Neal
|Born||September 12, 1956|
|Residence||Toronto, Ontario, Canada|
|Education||Ph.D in Computer Science, University of Toronto, 1995|
|Alma mater||University of Calgary, University of Toronto|
|Fields||Statistics, Machine Learning, Artificial Intelligence|
|Institutions||University of Toronto|
|Thesis||Bayesian Learning for Neural Networks (1995)|
|Doctoral advisor||Geoffrey Hinton|
Radford M. Neal is a professor at the Department of Statistics and Department of Computer Science at the University of Toronto, where he holds a research chair in statistics and machine learning. He studied computer science at the University of Calgary (B.Sc. 1977, M.Sc. 1980) and at the University of Toronto (Ph.D. 1995). He has made great contributions in the area of machine learning and statistics, where he is particular well known for his work on Markov chain Monte Carlo, error correcting codes and Bayesian learning for neural networks. He is also known for his blog and as the developer of pqR: a new version of the R interpreter.
- "Radford M. Neal Curriculum Vitae" (PDF). User radford at cs.utoronto.ca. Retrieved 4 May 2015.
- Neal, Radford (1993). Probabilistic Inference Using Markov Chain Monte Carlo Methods (PDF) (Report). Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto. p. 144. Retrieved 9 May 2015.
- Neal, Radford M (2011). "MCMC Using Hamiltonian Dynamics" (PDF). In Steve Brooks; Andrew Gelman; Galin L. Jones; Xiao-Li Meng. Handbook of Markov Chain Monte Carlo. Chapman and Hall/CRC. ISBN 0470177934.
- MacKay, D. J. C.; Neal, R. M. (1996). "Near Shannon limit performance of low density parity check codes". Electronics Letters. 32 (18): 1645. doi:10.1049/el:19961141.
- Neal, R. M. (1996). "Bayesian Learning for Neural Networks". Lecture Notes in Statistics. 118. doi:10.1007/978-1-4612-0745-0. ISBN 978-0-387-94724-2.
- "Radford Neal's blog". Retrieved 9 May 2015.
- "pqR - a pretty quick version of R". Retrieved 9 May 2015.
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