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Wessel Bruinsma
Wessel Bruinsma
Verified email at cam.ac.uk - Homepage
Title
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Cited by
Year
Convolutional Conditional Neural Processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
International Conference on Learning Representations (ICLR), 8th, 2020
722020
The Gaussian Process Autoregressive Regression Model (GPAR)
J Requeima, W Tebbutt, W Bruinsma, RE Turner
Artificial Intelligence and Statistics (AISTATS), 22nd International …, 2019
312019
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
AYK Foong, WP Bruinsma, J Gordon, Y Dubois, J Requeima, RE Turner
Advances in Neural Information Processing Systems (NeurIPS), 33th, 2020
242020
Scalable Exact Inference in Multi-Output Gaussian Processes
W Bruinsma, E Perim, W Tebbutt, S Hosking, A Solin, R Turner
International Conference on Machine Learning (ICML), 37th, 2020
172020
The Gaussian Neural Process
WP Bruinsma, J Requeima, AYK Foong, J Gordon, RE Turner
Advances in Approximate Bayesian Inference (AABI), 3rd Symposium on, 2021
152021
How Tight Can PAC-Bayes be in the Small Data Regime?
AYK Foong, WP Bruinsma, DR Burt, RE Turner
Advances in Neural Information Processing Systems (NeurIPS), 35th, 2021
62021
Efficient Gaussian Neural Processes for Regression
S Markou, J Requeima, W Bruinsma, R Turner
Uncertainty & Robustness in Deep Learning (UDL), ICML 2021 Workshop on, 2021
42021
Modelling Non-Smooth Signals with Complex Spectral Structure
WP Bruinsma, M Tegnér, RE Turner
International Conference on Artificial Intelligence and Statistics, 5166-5195, 2022
32022
Practical Conditional Neural Process Via Tractable Dependent Predictions
S Markou, J Requeima, W Bruinsma, A Vaughan, RE Turner
International Conference on Learning Representations (ICLR), 10th, 2022
32022
Wide Mean-Field Bayesian Neural Networks Ignore the Data
B Coker, WP Bruinsma, DR Burt, W Pan, F Doshi-Velez
Artificial Intelligence and Statistics (AISTATS), 25th International …, 2022
32022
Beamforming in Sparse, Random, 3D Array Antennas with Fluctuating Element Locations
MJ Bentum, IE Lager, S Bosma, WP Bruinsma, RP Hes
Antennas and Propagation (EuCAP), 9th European Conference on, 2015
32015
The Generalised Gaussian Process Convolution Model
W Bruinsma
University of Cambridge, 2016
22016
A Note on the Chernoff Bound for Random Variables in the Unit Interval
AYK Foong, WP Bruinsma, DR Burt
arXiv preprint arXiv:2205.07880, 2022
12022
The Gaussian Process Latent Autoregressive Model
R Xia, W Bruinsma, W Tebbutt, RE Turner
Advances in Approximate Bayesian Inference (AABI), 3rd Symposium on., 2020
12020
Learning Causally-Generated Stationary Time Series
W Bruinsma, RE Turner
arXiv preprint arXiv:1802.08167, 2018
12018
Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement
TR Andersson, WP Bruinsma, S Markou, DC Jones, JS Hosking, ...
Gaussian Processes, Spatiotemporal Modeling, and Decision-Making Systems …, 2022
2022
Sparse Gaussian Process Hyperparameters: Optimize or Integrate?
V Lalchand, WP Bruinsma, DR Burt, CE Rasmussen
Advances in Neural Information Processing Systems (NeurIPS), 36th, 2022
2022
Challenges and Pitfalls of Bayesian Unlearning
A Rawat, J Requeima, W Bruinsma, R Turner
Updatable Machine Learning (UpML), ICML 2022 Workshop on, 2022
2022
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models
P Berkovich, E Perim, W Bruinsma
Advanced in Approximate Bayesian Inference (AABI), 2nd Sympo- sium on, 2020
2020
Grating Lobes Prediction in 3D Array Antennas
S Bosma, WP Bruinsma, RP Hes, MJ Bentum, IE Lager
Antennas and Propagation (EuCAP), 11th European Conference on, 3733-3737, 2017
2017
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