Sally Cripps - RankMe

23 papers A* 2A 1B 1Journal 18Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Covariate Dependent Mixture of Bayesian Networks. CoRR Román Marchant, Dario Draca, Gilad Francis, Sahand Assadzadeh, Mathew Varidel, Frank Iorfino, Sally Cripps
2025	J	`jnl`	Plug-and-Play Model-Agnostic Counterfactual Policy Synthesis for Deep Reinforcement Learning-Based Recommendation. IEEE Trans. Neural Networks Learn. Syst. Siyu Wang, Xiaocong Chen, Julian J. McAuley, Sally Cripps, Lina Yao
2024	J	`jnl`	Optimal Particle-based Approximation of Discrete Distributions (OPAD). CoRR Hadi Mohasel Afshar, Gilad Francis, Sally Cripps
2023	J	`jnl`	Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning. CoRR Yun Li, Zhe Liu, Saurav Jha, Sally Cripps, Lina Yao
2022	J	`jnl`	AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series. J. Comput. Graph. Stat. Michael Bertolacci, Ori Rosen, Edward Cripps, Sally Cripps
2022	A*	`conf`	Fixed-Distance Hamiltonian Monte Carlo. NeurIPS Hadi Mohasel Afshar, Sally Cripps
2022	J	`jnl`	Remaining useful life prediction: A multiple product partition approach. Commun. Stat. Simul. Comput. John W. Lau, Edward Cripps, Sally Cripps
2021	A	`conf`	Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers. AISTATS Hadi Mohasel Afshar, Rafael Oliveira, Sally Cripps
2021	J	`jnl`	Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning. Environ. Model. Softw. Rohitash Chandra, Sally Cripps, Nathaniel Butterworth, R. Dietmar Müller
2019	J	`jnl`	Bayesian Nonparametric Adaptive Spectral Density Estimation for Financial Time Series. CoRR Nick James, Román Marchant, Richard Gerlach, Sally Cripps
2019	J	`jnl`	Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. Comput. Geosci. Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps
2019	J	`jnl`	Langevin-gradient parallel tempering for Bayesian neural learning. Neurocomputing Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps
2019	A*	`conf`	Structured Variational Inference in Continuous Cox Process Models. NeurIPS Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
2019	J	`jnl`	Structured Variational Inference in Continuous Cox Process Models. CoRR Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
2018	J	`jnl`	Applying machine learning to criminology: semi-parametric spatial-demographic Bayesian regression. Secur. Informatics Román Marchant, Sebastian Haan, Garner Clancey, Sally Cripps
2018	J	`jnl`	BayesLands: A Bayesian inference approach for parameter uncertainty quantification in Badlands. CoRR Rohitash Chandra, Danial Azam, R. Dietmar Müller, Tristan Salles, Sally Cripps
2018	J	`jnl`	BayesReef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics. CoRR Jodie Pall, Rohitash Chandra, Danial Azam, Tristan Salles, Jody M. Webster, Sally Cripps
2018	B	`conf`	Bayesian Multi-task Learning for Dynamic Time Series Prediction. IJCNN Rohitash Chandra, Sally Cripps
2018	J	`jnl`	Coevolutionary multi-task learning for feature-based modular pattern classification. Neurocomputing Rohitash Chandra, Sally Cripps
2018	J	`jnl`	Efficiency and robustness in Monte Carlo sampling of 3-D geophysical inversions with Obsidian v0.1.2: Setting up for success. CoRR Richard Scalzo, David Kohn, Hugo K. H. Olierook, Gregory Houseman, Rohitash Chandra, Mark A. Girolami, Sally Cripps
2018	J	`jnl`	Langevin-gradient parallel tempering for Bayesian neural learning. CoRR Rohitash Chandra, Konark Jain, Ratneel Vikash Deo, Sally Cripps
2018	J	`jnl`	Multi-core parallel tempering Bayeslands for basin and landscape evolution. CoRR Rohitash Chandra, R. Dietmar Müller, Ratneel Deo, Nathaniel Butterworth, Tristan Salles, Sally Cripps
2017	—	`conf`	Bayesian Neural Learning via Langevin Dynamics for Chaotic Time Series Prediction. ICONIP (5) Rohitash Chandra, Lamiae Azizi, Sally Cripps