Derek J. Posselt

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All published works

Action	Title	Year	Authors
+ PDF Chat	Temporal Multimodal Multivariate Learning	2022	Hyoshin Park Justice Darko Niharika Deshpande Venktesh Pandey Hui Su Masahiro Ono Dedrick Barkley Larkin Folsom Derek J. Posselt Steve Chien
+ PDF Chat	Optimal Estimation: Understanding Sources of Error When Retrieving Atmospheric Variables	2021	Maximilian Maahn David D. Turner Ulrich Löhnert Derek J. Posselt Kerstin Ebell Gerald G. Mace J. M. Comstock
+	Kernel embedded nonlinear observational mappings in the variational mapping particle filter.	2019	Manuel Pulido Peter Jan vanLeeuwen Derek J. Posselt
+ PDF Chat	Kernel Embedded Nonlinear Observational Mappings in the Variational Mapping Particle Filter	2019	Manuel Pulido Peter Jan van Leeuwen Derek J. Posselt
+	Kernel embedded nonlinear observational mappings in the variational mapping particle filter	2019	Manuel Pulido Fernández Peter Jan vanLeeuwen Derek J. Posselt
+	Markov Chain Monte Carlo Methods: Theory and Applications	2013	Derek J. Posselt

Common Coauthors

Coauthor	Papers Together
Manuel Pulido	2
Peter Jan vanLeeuwen	2
Larkin Folsom	1
Dedrick Barkley	1
Hui Su	1
Gerald G. Mace	1
Niharika Deshpande	1
David D. Turner	1
Manuel Pulido Fernández	1
Venktesh Pandey	1
Peter Jan van Leeuwen	1
Kerstin Ebell	1
J. M. Comstock	1
Maximilian Maahn	1
Steve Chien	1
Hyoshin Park	1
Ulrich Löhnert	1
Masahiro Ono	1
Justice Darko	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Inverse Problem Theory and Methods for Model Parameter Estimation	2005	Albert Tarantola	3
+	Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter	2018	Manuel Pulido Peter Jan vanLeeuwen	2
+	Derivative reproducing properties for kernel methods in learning theory	2007	Ding‐Xuan Zhou	2
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	2
+	Stochastic variational inference	2013	Matthew D. Hoffman David M. Blei Chong Wang John Paisley	2
+	Novel approach to nonlinear/non-Gaussian Bayesian state estimation	1993	Neil Gordon David Salmond A. F. M. Smith	2
+ PDF Chat	Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter	2007	Brian R. Hunt Eric J. Kostelich Istvan Szunyogh	2
+	Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images	1984	Stuart Geman Donald Geman	1
+ PDF Chat	Optimal Scaling of Discrete Approximations to Langevin Diffusions	1998	Gareth O. Roberts Jeffrey S. Rosenthal	1
+ PDF Chat	Weak convergence and optimal scaling of random walk Metropolis algorithms	1997	Susan A. Gelman Walter R. Gilks Gareth O. Roberts	1
+ PDF Chat	Annealing Markov Chain Monte Carlo with Applications to Ancestral Inference	1995	Charles J. Geyer E. A. Thompson	1
+	Examples of Adaptive MCMC	2009	Gareth O. Roberts Jeffrey S. Rosenthal	1
+	DRAM: Efficient adaptive MCMC	2006	Heikki Haario Marko Laine Antonietta Mira Eero Saksman	1
+	Sampling-Based Approaches to Calculating Marginal Densities	1990	Alan E. Gelfand A. F. M. Smith	1
+	Bayesian mixture modeling approach to account for heterogeneity in speed data	2010	Byung-Jung Park Yunlong Zhang Dominique Lord	1
+	Reversible jump Markov chain Monte Carlo computation and Bayesian model determination	1995	Peter J. Green	1
+	A Brief Survey of Bandwidth Selection for Density Estimation	1996	M. C. Jones J. S. Marron Simon J. Sheather	1
+	Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling	2009	Jasper A. Vrugt Cajo J. F. ter Braak Cees Diks B.A. Robinson James M. Hyman David Higdon	1
+	The BUGS project: Evolution, critique and future directions	2009	David J. Lunn David J. Spiegelhalter Andrew C. Thomas Nicky Best	1
+ PDF Chat	Markov Chains for Exploring Posterior Distributions	1994	Luke Tierney	1
+	Monte Carlo sampling methods using Markov chains and their applications	1970	W. Keith Hastings	1
+	The Calculation of Posterior Distributions by Data Augmentation	1987	Martin A. Tanner Wing Hung Wong	1
+ PDF Chat	An introduction to sampling via measure transport	2016	Youssef Marzouk Tarek Moselhy Matthew Parno Alessio Spantini	1
+	The Calculation of Posterior Distributions by Data Augmentation: Comment: A Noniterative Sampling/Importance Resampling Alternative to the Data Augmentation Algorithm for Creating a Few Imputations When Fractions of Missing Information Are Modest: The SIR Algorithm	1987	Donald B. Rubin	1
+	A Short History of MCMC: Subjective Recollections from Incomplete Data	2011	Christian P. Robert George Casella	1
+	Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm	2016	Qiang Liu Dilin Wang	1
+	Learning Combinatorial Optimization Algorithms over Graphs	2017	Hanjun Dai Elias B. Khalil Yuyu Zhang Bistra Dilkina Le Song	1
+	Horizon: Facebook's Open Source Applied Reinforcement Learning Platform	2018	Jason Gauci Edoardo Conti Yitao Liang Kittipat Virochsiri Yuchen He Zachary Kaden Vivek Narayanan Xiaohui Ye	1
+	Neural Combinatorial Optimization with Reinforcement Learning	2016	Irwan Bello Hieu Pham Quoc V. Le Mohammad Norouzi Samy Bengio	1
+	Variational Particle Approximations	2017	Ardavan Saeedi Tejas D. Kulkarni Vikash K. Mansinghka Samuel J. Gershman	1
+	Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm	2016	Qiang Liu Dilin Wang	1
+ PDF Chat	Machine learning for combinatorial optimization: A methodological tour d’horizon	2020	Yoshua Bengio Andrea Lodi Antoine Prouvost	1
+ PDF Chat	Markov Chain Monte Carlo: Can We Trust the Third Significant Figure?	2008	James M. Flegal Murali Haran Galin L. Jones	1
+	Adaptive proposal distribution for random walk Metropolis algorithm	1999	Heikki Haario Eero Saksman J. Tamminen	1
+	Sampling via Measure Transport: An Introduction	2017	Youssef Marzouk Tarek Moselhy Matthew Parno Alessio Spantini	1
+ PDF Chat	Handbook of Markov Chain Monte Carlo	2011	Steve Brooks Andrew Gelman Galin L. Jones Xiao‐Li Meng	1
+	MML mixture modelling of multi-state, Poisson, von Mises circular and Gaussian distributions	1997	Christopher S. Wallace David L. Dowe	1
+	Variational Particle Approximations	2014	Ardavan Saeedi Tejas D. Kulkarni Vikash K. Mansinghka Samuel J. Gershman	1
+ PDF Chat	Formulation, existence, and computation of boundedly rational dynamic user equilibrium with fixed or endogenous user tolerance	2015	Ke Han W.Y. Szeto Terry L. Friesz	1
+ PDF Chat	Validation of nonlinear inverse algorithms with Markov chain Monte Carlo method	2004	J. Tamminen	1
+ PDF Chat	An Adaptive Metropolis Algorithm	2001	Heikki Haario Eero Saksman J. Tamminen	1
+ PDF Chat	Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms	2007	Gareth O. Roberts Jeffrey S. Rosenthal	1
+	Optimal scaling for various Metropolis-Hastings algorithms	2001	Gareth O. Roberts Jeffrey S. Rosenthal	1