Kody J. H. Law

46 papers A* 1B 1Journal 44

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Exponential Concentration in Stochastic Approximation. Oper. Res. Kody J. H. Law, Neil Walton, Shangda Yang
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	J	`jnl`	Mixtures of Gaussian Process Experts with SMC^2. J. Mach. Learn. Res. Teemu Härkönen, Sara Wade, Kody J. H. Law, Lassi Roininen
2025	J	`jnl`	Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles. CoRR Xinzhu Liang, Joseph M. Lukens, Sanjaya Lohani, Brian T. Kirby, Thomas A. Searles, Xin Qiu, Kody J. H. Law
2024	A*	`conf`	Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. ICML Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin T. Carlberg, Neil Walton, Kody J. H. Law
2024	J	`jnl`	Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. CoRR Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Carlberg, Neil Walton, Kody J. H. Law
2024	J	`jnl`	Fast deep mixtures of Gaussian process experts. Mach. Learn. Clement Etienam, Kody J. H. Law, Sara Wade, Vitaly Zankin
2024	J	`jnl`	Multi-index Sequential Monte Carlo Ratio Estimators for Bayesian Inverse problems. Found. Comput. Math. Ajay Jasra, Kody J. H. Law, Neil Walton, Shangda Yang
2024	J	`jnl`	SMC Is All You Need: Parallel Strong Scaling. CoRR Xinzhu Liang, Sanjaya Lohani, Joseph M. Lukens, Brian T. Kirby, Thomas A. Searles, Kody J. H. Law
2023	J	`jnl`	A randomized multi-index sequential Monte Carlo method. Stat. Comput. Xinzhu Liang, Shangda Yang, Simon L. Cotter, Kody J. H. Law
2023	J	`jnl`	On Unbiased Estimation for Discretized Models. SIAM/ASA J. Uncertain. Quantification Jeremy Heng, Ajay Jasra, Kody J. H. Law, Alexander Tarakanov
2022	J	`jnl`	A randomized Multi-index sequential Monte Carlo method. CoRR Simon L. Cotter, Kody J. H. Law, Xinzhu Liang, Shangda Yang
2022	J	`jnl`	Bayesian Estimation of Oscillator Parameters: Toward Anomaly Detection and Cyber-Physical System Security. Sensors Joseph M. Lukens, Ali Passian, Srikanth B. Yoginath, Kody J. H. Law, Joel A. Dawson
2022	J	`jnl`	Certified dimension reduction in nonlinear Bayesian inverse problems. Math. Comput. Olivier Zahm, Tiangang Cui, Kody J. H. Law, Alessio Spantini, Youssef M. Marzouk
2022	J	`jnl`	Convergence Rates for Stochastic Approximation on a Boundary. CoRR Kody J. H. Law, Neil S. Walton, Shangda Yang
2022	J	`jnl`	Digital Fingerprinting of Microstructures. CoRR Michael D. White, Alexander Tarakanov, Christopher P. Race, Philip J. Withers, Kody J. H. Law
2022	J	`jnl`	Mixtures of Gaussian Process Experts with SMC CoRR Teemu Härkönen, Sara Wade, Kody J. H. Law, Lassi Roininen
2022	J	`jnl`	Multi-index Sequential Monte Carlo ratio estimators for Bayesian Inverse problems. CoRR Kody J. H. Law, Neil Walton, Shangda Yang, Ajay Jasra
2022	J	`jnl`	Multilevel Bayesian Deep Neural Networks. CoRR Neil K. Chada, Ajay Jasra, Kody J. H. Law, Sumeetpal S. Singh
2022	J	`jnl`	Sparse Online Variational Bayesian Regression. SIAM/ASA J. Uncertain. Quantification Kody J. H. Law, Vitaly Zankin
2021	J	`jnl`	Materials Fingerprinting Classification. CoRR Adam Spannaus, Kody J. H. Law, Piotr Luszczek, Farzana Nasrin, Cassie Putman Micucci, Peter K. Liaw, Louis Joseph Santodonato, David J. Keffer, Vasileios Maroulas
2021	J	`jnl`	Materials Fingerprinting Classification. Comput. Phys. Commun. Adam Spannaus, Kody J. H. Law, Piotr Luszczek, Farzana Nasrin, Cassie Putman Micucci, Peter K. Liaw, Louis Joseph Santodonato, David J. Keffer, Vasileios Maroulas
2021	J	`jnl`	Multilevel ensemble Kalman filtering for spatio-temporal processes. Numerische Mathematik Alexey Chernov, Håkon Hoel, Kody J. H. Law, Fabio Nobile, Raúl Tempone
2021	J	`jnl`	On Unbiased Estimation for Discretized Models. CoRR Jeremy Heng, Ajay Jasra, Kody J. H. Law, Alexander Tarakanov
2021	B	`conf`	Randomized Multilevel Monte Carlo for Embarrassingly Parallel Inference. SMC Ajay Jasra, Kody J. H. Law, Alexander Tarakanov, Fangyuan Yu
2021	J	`jnl`	Randomized multilevel Monte Carlo for embarrassingly parallel inference. CoRR Ajay Jasra, Kody J. H. Law, Fangyuan Yu
2021	J	`jnl`	Sparse online variational Bayesian regression. CoRR Kody J. H. Law, Vitaly Zankin
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
2021	J	`jnl`	Unbiased estimation of the gradient of the log-likelihood in inverse problems. Stat. Comput. Ajay Jasra, Kody J. H. Law, Lu Deng
2020	J	`jnl`	Ultra-fast Deep Mixtures of Gaussian Process Experts. CoRR Clement Etienam, Kody J. H. Law, Sara Wade
2020	J	`jnl`	Unbiased Filtering of a Class of Partially Observed Diffusions. CoRR Ajay Jasra, Kody J. H. Law, Fangyuan Yu
2019	J	`jnl`	Cluster, Classify, Regress: A General Method For Learning Discountinous Functions. CoRR David E. Bernholdt, Mark R. Cianciosa, Clement Etienam, David L. Green, Kody J. H. Law, Jin Myung Park
2019	J	`jnl`	Correction to: Multilevel particle filters for Lévy-driven stochastic differential equations. Stat. Comput. Ajay Jasra, Kody J. H. Law, Prince Peprah Osei
2019	J	`jnl`	Multilevel particle filters for Lévy-driven stochastic differential equations. Stat. Comput. Ajay Jasra, Kody J. H. Law, Prince Peprah Osei
2018	J	`jnl`	Accuracy of Some Approximate Gaussian Filters for the Navier-Stokes Equation in the Presence of Model Error. Multiscale Model. Simul. Michal Branicki, Andrew J. Majda, Kody J. H. Law
2018	J	`jnl`	Bayesian Static Parameter Estimation for Partially Observed Diffusions via Multilevel Monte Carlo. SIAM J. Sci. Comput. Ajay Jasra, Kengo Kamatani, Kody J. H. Law, Yan Zhou
2018	J	`jnl`	Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals. SIAM/ASA J. Uncertain. Quantification Alexandros Beskos, Ajay Jasra, Kody J. H. Law, Youssef M. Marzouk, Yan Zhou
2017	J	`jnl`	Multilevel Particle Filters. SIAM J. Numer. Anal. Ajay Jasra, Kengo Kamatani, Kody J. H. Law, Yan Zhou
2017	J	`jnl`	Multilevel Sequential Monte Carlo Samplers for Normalizing Constants. ACM Trans. Model. Comput. Simul. Pierre Del Moral, Ajay Jasra, Kody J. H. Law, Yan Zhou
2016	J	`jnl`	Accelerated Dimension-Independent Adaptive Metropolis. SIAM J. Sci. Comput. Yuxin Chen, David E. Keyes, Kody J. H. Law, Hatem Ltaief
2016	J	`jnl`	Deterministic Mean-Field Ensemble Kalman Filtering. SIAM J. Sci. Comput. Kody J. H. Law, Hamidou Tembine, Raúl Tempone
2016	J	`jnl`	Dimension-independent likelihood-informed MCMC. J. Comput. Phys. Tiangang Cui, Kody J. H. Law, Youssef M. Marzouk
2016	J	`jnl`	Multilevel ensemble Kalman filtering. SIAM J. Numer. Anal. Håkon Hoel, Kody J. H. Law, Raúl Tempone
2014	J	`jnl`	Proposals which speed up function-space MCMC. J. Comput. Appl. Math. Kody J. H. Law
2011	J	`jnl`	Evaluating Data Assimilation Algorithms CoRR Kody J. H. Law, Andrew M. Stuart
2010	J	`jnl`	Interaction of Excited States in Two-Species Bose-Einstein Condensates: A Case Study. SIAM J. Appl. Dyn. Syst. Todd Kapitula, Kody J. H. Law, Panayotis G. Kevrekidis