Sally Cripps

According to our database, Sally Cripps authored at least 18 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning.

Yun Li, Zhe Liu, Saurav Jha, Sally Cripps, Lina Yao

CoRR, 2023

2022

AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series.

Michael Bertolacci, Ori Rosen, Edward Cripps, Sally Cripps

J. Comput. Graph. Stat., January, 2022

Remaining useful life prediction: A multiple product partition approach.

John W. Lau, Edward Cripps, Sally Cripps

Commun. Stat. Simul. Comput., 2022

Fixed-Distance Hamiltonian Monte Carlo.

Hadi Mohasel Afshar, Sally Cripps

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning.

Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Müller

Environ. Model. Softw., 2021

Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers.

Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

<i>Bayesreef</i>: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics.

Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Richard Scalzo, Sally Cripps

Environ. Model. Softw., 2020

2019

Langevin-gradient parallel tempering for Bayesian neural learning.

Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps

Neurocomputing, 2019

Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands.

Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps

Comput. Geosci., 2019

Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series.

Nick James, Román Marchant, Richard Gerlach, Sally Cripps

CoRR, 2019

Structured Variational Inference in Continuous Cox Process Models.

Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression.

Román Marchant, Sebastian Haan, Garner Clancey, Sally Cripps

Secur. Informatics, 2018

Coevolutionary multi-task learning for feature-based modular pattern classification.

Rohitash Chandra, Sally Cripps

Neurocomputing, 2018

Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success.

Richard Scalzo, David Kohn, Hugo K. H. Olierook, Gregory Houseman, Rohitash Chandra, Mark A. Girolami, Sally Cripps

CoRR, 2018

BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics.

Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Sally Cripps

CoRR, 2018

Multi-core parallel tempering Bayeslands for basin and landscape evolution.

Rohitash Chandra, R. Dietmar Müller, Ratneel Deo, Nathaniel Butterworth, Tristan Salles, Sally Cripps

CoRR, 2018

Bayesian Multi-task Learning for Dynamic Time Series Prediction.

Rohitash Chandra, Sally Cripps

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017

Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction.

Rohitash Chandra, Lamiae Azizi, Sally Cripps

Proceedings of the Neural Information Processing - 24th International Conference, 2017