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Sally Cripps
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2020 – today
- 2023
- [i8]Yun Li, Zhe Liu, Saurav Jha, Sally Cripps, Lina Yao:
Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning. CoRR abs/2303.00404 (2023) - 2022
- [j8]John W. Lau
, Edward Cripps
, Sally Cripps:
Remaining useful life prediction: A multiple product partition approach. Commun. Stat. Simul. Comput. 51(9): 5288-5307 (2022) - [j7]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): 436-454 (2022) - [c5]Hadi Mohasel Afshar, Sally Cripps:
Fixed-Distance Hamiltonian Monte Carlo. NeurIPS 2022 - 2021
- [j6]Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Müller
:
Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning. Environ. Model. Softw. 139: 105002 (2021) - [c4]Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps:
Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers. AISTATS 2021: 1675-1683 - 2020
- [j5]Jodie Pall, Rohitash Chandra
, Danial Azam
, Tristan Salles
, Jody M. Webster
, Richard Scalzo, Sally Cripps:
Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. Environ. Model. Softw. 125: 104610 (2020)
2010 – 2019
- 2019
- [j4]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: 89-101 (2019) - [j3]Rohitash Chandra
, Konark Jain, Ratneel Vikash Deo
, Sally Cripps:
Langevin-gradient parallel tempering for Bayesian neural learning. Neurocomputing 359: 315-326 (2019) - [c3]Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps:
Structured Variational Inference in Continuous Cox Process Models. NeurIPS 2019: 12437-12447 - [i7]Nick James
, Román Marchant, Richard Gerlach, Sally Cripps:
Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series. CoRR abs/1902.03350 (2019) - [i6]Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps:
Structured Variational Inference in Continuous Cox Process Models. CoRR abs/1906.03161 (2019) - 2018
- [j2]Rohitash Chandra
, Sally Cripps:
Coevolutionary multi-task learning for feature-based modular pattern classification. Neurocomputing 319: 164-175 (2018) - [j1]Román Marchant, Sebastian Haan, Garner Clancey
, Sally Cripps:
Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression. Secur. Informatics 7(1): 1 (2018) - [c2]Rohitash Chandra
, Sally Cripps:
Bayesian Multi-task Learning for Dynamic Time Series Prediction. IJCNN 2018: 1-8 - [i5]Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps:
BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. CoRR abs/1805.03696 (2018) - [i4]Rohitash Chandra, R. Dietmar Müller, Ratneel Deo, Nathaniel Butterworth, Tristan Salles, Sally Cripps:
Multi-core parallel tempering Bayeslands for basin and landscape evolution. CoRR abs/1806.10939 (2018) - [i3]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 abs/1808.02763 (2018) - [i2]Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps:
Langevin-gradient parallel tempering for Bayesian neural learning. CoRR abs/1811.04343 (2018) - [i1]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 abs/1812.00318 (2018) - 2017
- [c1]Rohitash Chandra
, Lamiae Azizi, Sally Cripps:
Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction. ICONIP (5) 2017: 564-573
Coauthor Index
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