Robert Kohn - RankMe

35 papers A* 3A 2Misc 4Journal 25

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Variational Bayesian inference for models with nuisance parameters and an intractable likelihood. Stat. Comput. Y. H. Paco Tseng, Minh-Ngoc Tran, Robert Kohn
2024	A	`conf`	Contextual Directed Acyclic Graphs. AISTATS Ryan Thompson, Edwin V. Bonilla, Robert Kohn
2024	J	`jnl`	Flexible Variational Bayes Based on a Copula of a Mixture. J. Comput. Graph. Stat. David Gunawan, Robert Kohn, David J. Nott
2024	J	`jnl`	ProDAG: Projection-induced variational inference for directed acyclic graphs. CoRR Ryan Thompson, Edwin V. Bonilla, Robert Kohn
2024	J	`jnl`	Structured Variational Approximations with Skew Normal Decomposable Graphical Models and Implicit Copulas. J. Comput. Graph. Stat. Robert Salomone, Xuejun Yu, David J. Nott, Robert Kohn
2023	J	`jnl`	Automatically adapting the number of state particles in SMC Stat. Comput. Imke Botha, Robert Kohn, Leah F. South, Christopher C. Drovandi
2023	J	`jnl`	Contextual directed acyclic graphs. CoRR Ryan Thompson, Edwin V. Bonilla, Robert Kohn
2023	J	`jnl`	DeepVol: A Deep Transfer Learning Approach for Universal Asset Volatility Modeling. CoRR Chen Liu, Minh-Ngoc Tran, Chao Wang, Richard Gerlach, Robert Kohn
2023	J	`jnl`	Dynamic Mixture of Experts Models for Online Prediction. Technometrics Parfait Munezero, Mattias Villani, Robert Kohn
2023	J	`jnl`	Particle Mean Field Variational Bayes. CoRR Minh-Ngoc Tran, Paco Tseng, Robert Kohn
2023	J	`jnl`	Realized recurrent conditional heteroskedasticity model for volatility modelling. CoRR Chen Liu, Chao Wang, Minh-Ngoc Tran, Robert Kohn
2023	A*	`conf`	The Contextual Lasso: Sparse Linear Models via Deep Neural Networks. NeurIPS Ryan Thompson, Amir Dezfouli, Robert Kohn
2023	J	`jnl`	The Contextual Lasso: Sparse Linear Models via Deep Neural Networks. CoRR Ryan Thompson, Amir Dezfouli, Robert Kohn
2021	J	`jnl`	The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC. J. Comput. Graph. Stat. Matias Quiroz, Minh-Ngoc Tran, Mattias Villani, Robert Kohn, Khue-Dung Dang
2020	J	`jnl`	A flexible particle Markov chain Monte Carlo method. Stat. Comput. Eduardo F. Mendes, Christopher K. Carter, David Gunawan, Robert Kohn
2020	A*	`conf`	Spectral Subsampling MCMC for Stationary Time Series. ICML Robert Salomone, Matias Quiroz, Robert Kohn, Mattias Villani, Minh-Ngoc Tran
2020	J	`jnl`	Subsampling sequential Monte Carlo for static Bayesian models. Stat. Comput. David Gunawan, Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran
2019	J	`jnl`	Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins. Stat. Comput. David Gunawan, Minh-Ngoc Tran, Kosuke Suzuki, Josef Dick, Robert Kohn
2019	J	`jnl`	Hamiltonian Monte Carlo with Energy Conserving Subsampling. J. Mach. Learn. Res. Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran, Mattias Villani
2019	A	`conf`	Variance reduction properties of the reparameterization trick. AISTATS Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson
2018	J	`jnl`	On some variance reduction properties of the reparameterization trick. CoRR Ming Xu, Matias Quiroz, Robert Kohn, Scott A. Sisson
2016	J	`jnl`	Adaptive Metropolis-Hastings sampling using reversible dependent mixture proposals. Stat. Comput. Minh-Ngoc Tran, Michael K. Pitt, Robert Kohn
2015	—	`—`	A Framework for Batch Scheduling with Variable Neighborhood Search in Wafer Fabrication. Robert Kohn
2013	Misc	`conf`	Study on multi-objective optimization for parallel batch machine scheduling using variable neighbourhood search. WSC Robert Kohn, Oliver Rose, Christoph Laroque
2012	Misc	`conf`	Study on optimization potential influencing factors in simulation studies focused on parallel batch machine scheduling using variable neighbourhood search. WSC Robert Kohn, Oliver Rose
2011	Misc	`conf`	Automated generation of analytical process time models for cluster tools in semiconductor manufacturing. WSC Robert Kohn, Oliver Rose
2011	J	`jnl`	Constructing priors based on model size for nondecomposable Gaussian graphical models: A simulation based approach. J. Multivar. Anal. Christopher K. Carter, Frederick Wong, Robert Kohn
2010	J	`jnl`	Bayesian variable selection and model averaging in the arbitrage pricing theory model. Comput. Stat. Data Anal. Rachida Ouysse, Robert Kohn
2009	J	`jnl`	Bayesian covariance matrix estimation using a mixture of decomposable graphical models. Stat. Comput. Helen Armstrong, Christopher K. Carter, Kin Foon Kevin Wong, Robert Kohn
2009	Misc	`conf`	Evaluation of Modeling, Simulation and Optimization Approaches for Work Flow Management in Semiconductor Manufacturing. WSC Robert Kohn, Daniel Noack, Marcin Mosinski, Zhugen Zhou, Oliver Rose
2007	J	`jnl`	A general approach to heteroscedastic linear regression. Stat. Comput. David S. Leslie, Robert Kohn, David J. Nott
2003	J	`jnl`	Estimation and variable selection in nonparametric heteroscedastic regression. Stat. Comput. Paul Yau, Robert Kohn
2003	J	`jnl`	Representation and Self-Similarity of Shapes. IEEE Trans. Pattern Anal. Mach. Intell. Davi Geiger, Tyng-Luh Liu, Robert Kohn
2001	J	`jnl`	Nonparametric regression using linear combinations of basis functions. Stat. Comput. Robert Kohn, Michael S. Smith, David Chan
1998	A*	`conf`	Representation and Self-Similarity of Shapes. ICCV Tyng-Luh Liu, Davi Geiger, Robert Kohn