Sally Cripps

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 21

Top Topics

Bayesian Inference

Top Venues

Environ. Model. Softw.

Publications

Yun Li, Zhe Liu, Saurav Jha, Sally Cripps, Lina Yao
Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning. CoRR (2023)
Hadi Mohasel Afshar, Sally Cripps
Fixed-Distance Hamiltonian Monte Carlo. NeurIPS (2022)
Michael Bertolacci, Ori Rosen, Edward Cripps, Sally Cripps
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series. J. Comput. Graph. Stat. 31 (1) (2022)
John W. Lau, Edward Cripps, Sally Cripps
Remaining useful life prediction: A multiple product partition approach. Commun. Stat. Simul. Comput. 51 (9) (2022)
Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps
Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers. AISTATS (2021)
Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Müller
Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning. Environ. Model. Softw. 139 (2021)
Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Richard Scalzo, Sally Cripps
: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. Environ. Model. Softw. 125 (2020)
Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. Comput. Geosci. 131 (2019)
Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
Structured Variational Inference in Continuous Cox Process Models. CoRR (2019)
Nick James, Román Marchant, Richard Gerlach, Sally Cripps
Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series. CoRR (2019)
Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps
Langevin-gradient parallel tempering for Bayesian neural learning. Neurocomputing 359 (2019)
Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
Structured Variational Inference in Continuous Cox Process Models. NeurIPS (2019)
Rohitash Chandra, Sally Cripps
Bayesian Multi-task Learning for Dynamic Time Series Prediction. IJCNN (2018)
Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. CoRR (2018)
Rohitash Chandra, R. Dietmar Müller, Ratneel Deo, Nathaniel Butterworth, Tristan Salles, Sally Cripps
Multi-core parallel tempering Bayeslands for basin and landscape evolution. CoRR (2018)
Richard Scalzo, David Kohn, Hugo K. H. Olierook, Gregory Houseman, Rohitash Chandra, Mark A. Girolami, Sally Cripps
Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. CoRR (2018)
Román Marchant, Sebastian Haan, Garner Clancey, Sally Cripps
Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression. Secur. Informatics 7 (1) (2018)
Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps
Langevin-gradient parallel tempering for Bayesian neural learning. CoRR (2018)
Rohitash Chandra, Sally Cripps
Coevolutionary multi-task learning for feature-based modular pattern classification. Neurocomputing 319 (2018)
Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Sally Cripps
BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. CoRR (2018)
Rohitash Chandra, Lamiae Azizi, Sally Cripps
Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction. ICONIP (5) (2017)