Andrew Warrington

21 papers A* 6A 1Journal 14

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Foundation Artificial Intelligence Models for Health Recognition Using Face Photographs (FAHR-Face). CoRR Fridolin Haugg, Grace Lee, John He, Leonard Nürnberg, Dennis Bontempi, Danielle S. Bitterman, Paul J. Catalano, Vasco Prudente, Dmitrii Glubokov, Andrew Warrington, Suraj Pai, Dirk De Ruysscher, Christian V. Guthier, Benjamin H. Kann, Vadim N. Gladyshev, Hugo J. W. L. Aerts, Raymond H. Mak
2025	J	`jnl`	Hyper Hawkes Processes: Interpretable Models of Marked Temporal Point Processes. CoRR Alex Boyd, Andrew Warrington, Taha A. Kass-Hout, Parminder Bhatia, Danica Xiao
2024	J	`jnl`	Deep Linear Hawkes Processes. CoRR Yuxin Chang, Alex Boyd, Cao Xiao, Taha A. Kass-Hout, Parminder Bhatia, Padhraic Smyth, Andrew Warrington
2024	A*	`conf`	Towards Scalable and Stable Parallelization of Nonlinear RNNs. NeurIPS Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith, Scott W. Linderman
2024	J	`jnl`	Towards Scalable and Stable Parallelization of Nonlinear RNNs. CoRR Xavier Gonzalez, Andrew Warrington, Jimmy T. H. Smith, Scott W. Linderman
2023	A*	`conf`	Simplified State Space Layers for Sequence Modeling. ICLR Jimmy T. H. Smith, Andrew Warrington, Scott W. Linderman
2023	A*	`conf`	Switching Autoregressive Low-rank Tensor Models. NeurIPS Hyun Dong Lee, Andrew Warrington, Joshua I. Glaser, Scott W. Linderman
2023	J	`jnl`	Switching Autoregressive Low-rank Tensor Models. CoRR Hyun Dong Lee, Andrew Warrington, Joshua I. Glaser, Scott W. Linderman
2022	A*	`conf`	SIXO: Smoothing Inference with Twisted Objectives. NeurIPS Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott W. Linderman
2022	J	`jnl`	SIXO: Smoothing Inference with Twisted Objectives. CoRR Dieterich Lawson, Allan Raventós, Andrew Warrington, Scott W. Linderman
2022	J	`jnl`	Simplified State Space Layers for Sequence Modeling. CoRR Jimmy T. H. Smith, Andrew Warrington, Scott W. Linderman
2021	J	`jnl`	Planning as Inference in Epidemiological Dynamics Models. Frontiers Artif. Intell. Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, John Grefenstette, Duncan Campbell, Seyed Ali Nasseri
2021	A*	`conf`	Robust Asymmetric Learning in POMDPs. ICML Andrew Warrington, Jonathan Wilder Lavington, Adam Scibior, Mark Schmidt, Frank Wood
2020	A	`conf`	Coping With Simulators That Don't Always Return. AISTATS Andrew Warrington, Frank Wood, Saeid Naderiparizi
2020	J	`jnl`	Coping With Simulators That Don't Always Return. CoRR Andrew Warrington, Saeid Naderiparizi, Frank Wood
2020	J	`jnl`	Planning as Inference in Epidemiological Models. CoRR Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, Seyed Ali Nasseri
2020	J	`jnl`	Robust Asymmetric Learning in POMDPs. CoRR Andrew Warrington, J. Wilder Lavington, Adam Scibior, Mark Schmidt, Frank Wood
2019	J	`jnl`	The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging. CoRR Andrew Warrington, Arthur P. C. Spencer, Frank Wood
2018	J	`jnl`	Generalising Cost-Optimal Particle Filtering. CoRR Andrew Warrington, Neil Dhir
2018	A*	`conf`	On Nesting Monte Carlo Estimators. ICML Tom Rainforth, Robert Cornish, Hongseok Yang, Andrew Warrington
2017	J	`jnl`	Updating the VESICLE-CNN Synapse Detector. CoRR Andrew Warrington, Frank D. Wood