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2020 – today
- 2024
[j24]Ajay Jasra
, Kody J. H. Law, Neil Walton, Shangda Yang:
Multi-index Sequential Monte Carlo Ratio Estimators for Bayesian Inverse problems. Found. Comput. Math. 24(4): 1249-1304 (2024)- [j23]Clement Etienam, Kody J. H. Law, Sara Wade, Vitaly Zankin:
Fast deep mixtures of Gaussian process experts. Mach. Learn. 113(3): 1483-1508 (2024) - [c2]Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin T. Carlberg, Neil Walton, Kody J. H. Law:
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. ICML 2024 - [i16]Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Carlberg, Neil Walton, Kody J. H. Law:
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. CoRR abs/2402.02111 (2024) - [i15]Xinzhu Liang, Sanjaya Lohani, Joseph M. Lukens, Brian T. Kirby, Thomas A. Searles, Kody J. H. Law:
SMC Is All You Need: Parallel Strong Scaling. CoRR abs/2402.06173 (2024) - 2023
- [j22]Jeremy Heng, Ajay Jasra, Kody J. H. Law, Alexander Tarakanov:
On Unbiased Estimation for Discretized Models. SIAM/ASA J. Uncertain. Quantification 11(2): 616-645 (2023) - [j21]Xinzhu Liang, Shangda Yang, Simon L. Cotter, Kody J. H. Law:
A randomized multi-index sequential Monte Carlo method. Stat. Comput. 33(5): 97 (2023) - 2022
- [j20]Kody J. H. Law, Vitaly Zankin:
Sparse Online Variational Bayesian Regression. SIAM/ASA J. Uncertain. Quantification 10(1): 1070-1100 (2022) - [j19]Olivier Zahm, Tiangang Cui, Kody J. H. Law, Alessio Spantini, Youssef M. Marzouk:
Certified dimension reduction in nonlinear Bayesian inverse problems. Math. Comput. 91(336): 1789-1835 (2022) - [j18]Joseph M. Lukens, Ali Passian, Srikanth B. Yoginath, Kody J. H. Law, Joel A. Dawson:
Bayesian Estimation of Oscillator Parameters: Toward Anomaly Detection and Cyber-Physical System Security. Sensors 22(16): 6112 (2022) - [i14]Kody J. H. Law, Neil Walton, Shangda Yang, Ajay Jasra:
Multi-index Sequential Monte Carlo ratio estimators for Bayesian Inverse problems. CoRR abs/2203.05351 (2022) - [i13]Neil K. Chada, Ajay Jasra, Kody J. H. Law, Sumeetpal S. Singh:
Multilevel Bayesian Deep Neural Networks. CoRR abs/2203.12961 (2022) - [i12]Michael D. White, Alexander Tarakanov, Christopher P. Race, Philip J. Withers, Kody J. H. Law:
Digital Fingerprinting of Microstructures. CoRR abs/2203.13718 (2022) - [i11]Kody J. H. Law, Neil S. Walton, Shangda Yang:
Convergence Rates for Stochastic Approximation on a Boundary. CoRR abs/2208.07243 (2022) - [i10]Teemu Härkönen, Sara Wade, Kody J. H. Law, Lassi Roininen:
Mixtures of Gaussian Process Experts with SMC2. CoRR abs/2208.12830 (2022) - [i9]Simon L. Cotter, Kody J. H. Law, Xinzhu Liang, Shangda Yang:
A randomized Multi-index sequential Monte Carlo method. CoRR abs/2210.15390 (2022) - 2021
- [j17]Adam Spannaus, Kody J. H. Law, Piotr Luszczek, Farzana Nasrin, Cassie Putman Micucci, Peter K. Liaw, Louis Joseph Santodonato, David J. Keffer, Vasileios Maroulas:
Materials Fingerprinting Classification. Comput. Phys. Commun. 266: 108019 (2021) - [j16]Neil K. Chada, Jordan Franks, Ajay Jasra, Kody J. H. Law, Matti Vihola:
Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions. SIAM/ASA J. Uncertain. Quantification 9(2): 763-787 (2021) - [j15]Alexey Chernov, Håkon Hoel, Kody J. H. Law, Fabio Nobile, Raúl Tempone:
Multilevel ensemble Kalman filtering for spatio-temporal processes. Numerische Mathematik 147(1): 71-125 (2021) - [j14]Ajay Jasra, Kody J. H. Law, Deng Lu:
Unbiased estimation of the gradient of the log-likelihood in inverse problems. Stat. Comput. 31(3): 21 (2021) - [c1]Ajay Jasra, Kody J. H. Law, Alexander Tarakanov, Fangyuan Yu:
Randomized Multilevel Monte Carlo for Embarrassingly Parallel Inference. SMC 2021: 3-21 - [i8]Adam Spannaus, Kody J. H. Law, Piotr Luszczek, Farzana Nasrin, Cassie Putman Micucci, Peter K. Liaw, Louis Joseph Santodonato, David J. Keffer, Vasileios Maroulas:
Materials Fingerprinting Classification. CoRR abs/2101.05808 (2021) - [i7]Jeremy Heng, Ajay Jasra, Kody J. H. Law, Alexander Tarakanov:
On Unbiased Estimation for Discretized Models. CoRR abs/2102.12230 (2021) - [i6]Kody J. H. Law, Vitaly Zankin:
Sparse online variational Bayesian regression. CoRR abs/2102.12261 (2021) - [i5]Ajay Jasra, Kody J. H. Law, Fangyuan Yu:
Randomized multilevel Monte Carlo for embarrassingly parallel inference. CoRR abs/2107.01913 (2021) - 2020
- [i4]Ajay Jasra, Kody J. H. Law, Fangyuan Yu:
Unbiased Filtering of a Class of Partially Observed Diffusions. CoRR abs/2002.03747 (2020) - [i3]Clement Etienam, Kody J. H. Law, Sara Wade:
Ultra-fast Deep Mixtures of Gaussian Process Experts. CoRR abs/2006.13309 (2020)
2010 – 2019
- 2019
- [j13]Ajay Jasra, Kody J. H. Law, Prince Peprah Osei:
Multilevel particle filters for Lévy-driven stochastic differential equations. Stat. Comput. 29(4): 775-789 (2019) - [j12]Ajay Jasra, Kody J. H. Law, Prince Peprah Osei:
Correction to: Multilevel particle filters for Lévy-driven stochastic differential equations. Stat. Comput. 29(4): 851 (2019) - [i2]David E. Bernholdt, Mark R. Cianciosa, Clement Etienam, David L. Green, Kody J. H. Law, Jin Myung Park:
Cluster, Classify, Regress: A General Method For Learning Discountinous Functions. CoRR abs/1905.06220 (2019) - 2018
- [j11]Alexandros Beskos, Ajay Jasra, Kody J. H. Law, Youssef M. Marzouk, Yan Zhou:
Multilevel Sequential Monte Carlo with Dimension-Independent Likelihood-Informed Proposals. SIAM/ASA J. Uncertain. Quantification 6(2): 762-786 (2018) - [j10]Michal Branicki, Andrew J. Majda, Kody J. H. Law:
Accuracy of Some Approximate Gaussian Filters for the Navier-Stokes Equation in the Presence of Model Error. Multiscale Model. Simul. 16(4): 1756-1794 (2018) - [j9]Ajay Jasra, Kengo Kamatani, Kody J. H. Law, Yan Zhou:
Bayesian Static Parameter Estimation for Partially Observed Diffusions via Multilevel Monte Carlo. SIAM J. Sci. Comput. 40(2) (2018) - 2017
- [j8]Ajay Jasra, Kengo Kamatani, Kody J. H. Law, Yan Zhou:
Multilevel Particle Filters. SIAM J. Numer. Anal. 55(6): 3068-3096 (2017) - [j7]Pierre Del Moral, Ajay Jasra, Kody J. H. Law, Yan Zhou:
Multilevel Sequential Monte Carlo Samplers for Normalizing Constants. ACM Trans. Model. Comput. Simul. 27(3): 20 (2017) - 2016
- [j6]Tiangang Cui, Kody J. H. Law, Youssef M. Marzouk:
Dimension-independent likelihood-informed MCMC. J. Comput. Phys. 304: 109-137 (2016) - [j5]Håkon Hoel, Kody J. H. Law, Raúl Tempone:
Multilevel ensemble Kalman filtering. SIAM J. Numer. Anal. 54(3): 1813-1839 (2016) - [j4]Kody J. H. Law, Hamidou Tembine, Raúl Tempone:
Deterministic Mean-Field Ensemble Kalman Filtering. SIAM J. Sci. Comput. 38(3) (2016) - [j3]Yuxin Chen, David E. Keyes, Kody J. H. Law, Hatem Ltaief:
Accelerated Dimension-Independent Adaptive Metropolis. SIAM J. Sci. Comput. 38(5) (2016) - 2014
- [j2]Kody J. H. Law:
Proposals which speed up function-space MCMC. J. Comput. Appl. Math. 262: 127-138 (2014) - 2011
- [i1]Kody J. H. Law, Andrew M. Stuart:
Evaluating Data Assimilation Algorithms. CoRR abs/1107.4118 (2011) - 2010
- [j1]Todd Kapitula, Kody J. H. Law, Panayotis G. Kevrekidis:
Interaction of Excited States in Two-Species Bose-Einstein Condensates: A Case Study. SIAM J. Appl. Dyn. Syst. 9(1): 34-61 (2010)
Coauthor Index
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