Ari Pakman

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Liam PaninskiColumbia UniversityVerified email at stat.columbia.edu
Leonardo RastelliYITP, Stony Brook UniversityVerified email at stonybrook.edu
Shlomo S. RazamatTechnionVerified email at physics.technion.ac.il
Sunil MukhiIISER PuneVerified email at iiserpune.ac.in
Yueqi WangGoogleVerified email at google.com
Dar GilboaGoogleVerified email at google.com
Roy FoxAssistant Professor, UC IrvineVerified email at uci.edu
Eftychios A. PnevmatikakisReality labs at MetaVerified email at flatironinstitute.org
Mariano Ignacio GabittoAllen Institute for Brain SciencesVerified email at alleninstitute.org
David E. CarlsonAssistant Professor, Duke UniversityVerified email at duke.edu
Fidel A. SchaposnikDepartamento de Física, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, ArgentinaVerified email at fisica.unlp.edu.ar
Nicolas GrandiIFLP-Conicet, Departamento de Física-UNLPVerified email at fisica.unlp.edu.ar
Andrei ParnachevTrinity College DublinVerified email at maths.tcd.ie
Catalin MitelutColumbia UniversityVerified email at alumni.ubc.ca
Josh MerelMeta Reality LabsVerified email at google.com
Gaston GiribetNew York UniversityVerified email at nyu.edu
L F AbbottBrandeis University, CERN, Boston University, Columbia University, Stanford Linear AcceleratorVerified email at columbia.edu
Jay BikoffAssistant Member, St. Jude Children's Research HospitalVerified email at stjude.org
Brooks PaigeAssociate Professor, University College LondonVerified email at ucl.ac.uk
Jonathan HugginsAssistant Professor of Statistics, Boston UniversityVerified email at bu.edu

Ari Pakman

Ben-Gurion University

Verified email at bgu.ac.il - Homepage

Machine Learning Statistics Physics Neuroscience


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
FZZ algebra A Mukherjee, S Mukhi, A Pakman Journal of High Energy Physics 2007 (01), 025, 2007	640	2007
Taming the Noise in Reinforcement Learning via Soft Updates R Fox, A Pakman, N Tishby 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016	301	2016
Exact Hamiltonian Monte Carlo for Truncated Multivariate Gaussians A Pakman, L Paninski Journal of Computational and Graphical Statistics, 2012	218	2012
Diagrams for symmetric product orbifolds A Pakman, L Rastelli, SS Razamat Journal of High Energy Physics 2009 (10), 034, 2009	118	2009
Exact chiral ring of AdS₃/CFT₂ A Dabholkar, A Pakman Advances in Theoretical and Mathematical Physics 13 (2), 409-462, 2009	113	2009
Topological entanglement entropy and holography A Pakman, A Parnachev Journal of High Energy Physics 2008 (07), 097, 2008	93	2008
Extremal correlators and Hurwitz numbers in symmetric product orbifolds A Pakman, L Rastelli, SS Razamat Physical Review D 80 (8), 086009, 2009	80	2009
Auxiliary-variable exact Hamiltonian Monte Carlo samplers for binary distributions A Pakman, L Paninski Advances in Neural Information Processing Systems (NIPS) 26, 2490–2498, 2013	79	2013
A spin chain for the symmetric product CFT2 A Pakman, L Rastelli, SS Razamat Journal of High Energy Physics 2010 (5), 1-48, 2010	79	2010
Bayesian spike inference from calcium imaging data EA Pnevmatikakis, J Merel, A Pakman, L Paninski 2013 Asilomar Conference on Signals, Systems and Computers, 349-353, 2013	75	2013
The partition function of the supersymmetric two-dimensional black hole and little string theory D Israël, C Kounnas, A Pakman, J Troost Journal of High Energy Physics 2004 (06), 033, 2004	75	2004
Exact N= 4 correlators of AdS3/CFT2 A Pakman, A Sever Physics Letters B 652 (1), 60-62, 2007	73	2007
D-branes in N=2 Liouville theory and its mirror D Israël, A Pakman, J Troost Nuclear physics B 710 (3), 529-576, 2005	69	2005
Spectral flow in AdS3/CFT2 G Giribet, A Pakman, L Rastelli Journal of High Energy Physics 2008 (06), 013, 2008	63	2008
Bayesian Sparse Regression Analysis Documents the Diversity of Spinal Inhibitory Interneurons MI Gabitto, A Pakman, JB Bikoff*, LF Abbott, TM Jessell, L Paninski Cell, 2016	59	2016
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits B Shababo, B Paige, A Pakman, L Paninski Advances in Neural Information Processing Systems 26, 1304-1312, 2013	45	2013
Type 0 strings in a 2-d black hole A Giveon, A Konechny, A Pakman, A Sever Journal of High Energy Physics 2003 (10), 025, 2003	45	2003
D-branes in little string theory D Israël, A Pakman, J Troost Nuclear Physics B 722 (1-2), 3-64, 2005	44	2005
More on superstrings in AdS3×M A Giveon, A Pakman Journal of High Energy Physics, 056, 2003	44*	2003
BRST quantization of string theory in AdS3 A Pakman Journal of High Energy Physics 2003 (06), 053, 2003	37	2003

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