Neil K. Chada - RankMe

36 papers A 2Journal 34

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Kinetic Langevin Splitting Schemes for Constrained Sampling. CoRR Neil K. Chada, Lu Yu
2026	J	`jnl`	Unbiased parameter estimation for bayesian inverse problems. Stat. Comput. Neil K. Chada, Ajay Jasra, Mohamed Maama, Raúl Tempone
2025	J	`jnl`	Bayesian Deep Learning with Multilevel Trace-Class Neural Networks. SIAM J. Math. Data Sci. Neil K. Chada, Ajay Jasra, Kody J. H. Law, Sumeetpal S. Singh
2025	A	`conf`	Decoupling epistemic and aleatoric uncertainties with possibility theory. AISTATS Nong Minh Hieu, Jeremie Houssineau, Neil K. Chada, Emmanuel Delande
2025	A	`conf`	Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics. AISTATS Daniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler
2024	J	`jnl`	A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators. J. Mach. Learn. Res. Neil K. Chada, Quanjun Lang, Fei Lu, Xiong Wang
2024	J	`jnl`	A Stochastic Iteratively Regularized Gauss-Newton Method. CoRR El Houcine Bergou, Neil K. Chada, Youssef Diouane
2024	J	`jnl`	Learning dynamical systems from data: Gradient-based dictionary optimization. CoRR Mohammad Tabish, Neil K. Chada, Stefan Klus
2024	J	`jnl`	Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics. CoRR Daniel Paulin, Peter A. Whalley, Neil K. Chada, Benedict J. Leimkuhler
2024	J	`jnl`	The Ensemble Kalman Filter for Dynamic Inverse Problems. CoRR Simon Weissmann, Neil K. Chada, Xin T. Tong
2024	J	`jnl`	Unbiased Approximations for Stationary Distributions of McKean-Vlasov SDEs. CoRR Elsiddig Awadelkarim, Neil K. Chada, Ajay Jasra
2023	J	`jnl`	On a Dynamic Variant of the Iteratively Regularized Gauss-Newton Method with Sequential Data. SIAM J. Sci. Comput. Neil K. Chada, Marco A. Iglesias, Shuai Lu, Frank Werner
2023	J	`jnl`	The Stochastic Steepest Descent Method for Robust Optimization in Banach Spaces. CoRR Neil K. Chada, Philip J. Herbert
2023	J	`jnl`	Unbiased Estimation Using Underdamped Langevin Dynamics. SIAM J. Sci. Comput. Hamza M. Ruzayqat, Neil K. Chada, Ajay Jasra
2023	J	`jnl`	Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients. CoRR Neil K. Chada, Benedict J. Leimkuhler, Daniel Paulin, Peter A. Whalley
2022	J	`jnl`	A Data-Adaptive Prior for Bayesian Learning of Kernels in Operators. CoRR Neil K. Chada, Quanjun Lang, Fei Lu, Xiong Wang
2022	J	`jnl`	A Review of the EnKF for Parameter Estimation. CoRR Neil K. Chada
2022	J	`jnl`	Cauchy Markov random field priors for Bayesian inversion. Stat. Comput. Jarkko Suuronen, Neil K. Chada, Lassi Roininen
2022	J	`jnl`	Convergence acceleration of ensemble Kalman inversion in nonlinear settings. Math. Comput. Neil K. Chada, Xin T. Tong
2022	J	`jnl`	Improved Efficiency of Multilevel Monte Carlo for Stochastic PDE through Strong Pairwise Coupling. J. Sci. Comput. Neil K. Chada, Håkon Hoel, Ajay Jasra, Georgios E. Zouraris
2022	J	`jnl`	Multilevel Bayesian Deep Neural Networks. CoRR Neil K. Chada, Ajay Jasra, Kody J. H. Law, Sumeetpal S. Singh
2022	J	`jnl`	Multilevel Ensemble Kalman-Bucy Filters. SIAM/ASA J. Uncertain. Quantification Neil K. Chada, Ajay Jasra, Fangyuan Yu
2022	J	`jnl`	Multilevel estimation of normalization constants using ensemble Kalman-Bucy filters. Stat. Comput. Hamza M. Ruzayqat, Neil K. Chada, Ajay Jasra
2022	J	`jnl`	On a Dynamic Variant of the Iteratively Regularized Gauss-Newton Method with Sequential Data. CoRR Neil K. Chada, Marco A. Iglesias, Shuai Lu, Frank Werner
2022	J	`jnl`	Unbiased Estimation of the Vanilla and Deterministic Ensemble Kalman-Bucy Filters. CoRR Miguel Alvarez, Neil K. Chada, Ajay Jasra
2021	J	`jnl`	Adaptive Tikhonov strategies for stochastic ensemble Kalman inversion. CoRR Simon Weissmann, Neil K. Chada, Claudia Schillings, Xin T. Tong
2021	J	`jnl`	Improved efficiency of multilevel Monte Carlo for stochastic PDE through strong pairwise coupling. CoRR Neil K. Chada, Håkon Hoel, Ajay Jasra, Georgios E. Zouraris
2021	J	`jnl`	Multilevel Estimation of Normalization Constants Using the Ensemble Kalman-Bucy Filter. CoRR Hamza M. Ruzayqat, Neil K. Chada, Ajay Jasra
2021	J	`jnl`	Unbiased Estimation of the Hessian for Partially Observed Diffusions. CoRR Neil K. Chada, Ajay Jasra, Fangyuan Yu
2021	J	`jnl`	Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions. SIAM/ASA J. Uncertain. Quantification Neil K. Chada, Jordan Franks, Ajay Jasra, Kody J. H. Law, Matti Vihola
2020	J	`jnl`	Consistency analysis of bilevel data-driven learning in inverse problems. CoRR Neil K. Chada, Claudia Schillings, Xin T. Tong, Simon Weissmann
2020	J	`jnl`	Iterative Ensemble Kalman Methods: A Unified Perspective with Some New Variants. CoRR Neil K. Chada, Yuming Chen, Daniel Sanz-Alonso
2020	J	`jnl`	Multilevel Ensemble Kalman-Bucy Filters. CoRR Neil K. Chada, Ajay Jasra, Fangyuan Yu
2020	J	`jnl`	Tikhonov Regularization within Ensemble Kalman Inversion. SIAM J. Numer. Anal. Neil K. Chada, Andrew M. Stuart, Xin T. Tong
2019	J	`jnl`	Convergence Acceleration of Ensemble Kalman Inversion in Nonlinear Settings. CoRR Neil K. Chada, Xin T. Tong
2019	J	`jnl`	On the Incorporation of Box-Constraints for Ensemble Kalman Inversion. CoRR Neil K. Chada, Claudia Schillings, Simon Weissmann