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ORCIDWessel P. Bruinsma
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2020 – today
- 2024
[c13]Matthew Ashman, Cristiana Diaconu, Junhyuck Kim, Lakee Sivaraya, Stratis Markou, James Requeima, Wessel P. Bruinsma, Richard E. Turner:
Translation Equivariant Transformer Neural Processes. ICML 2024- [c12]Isabel Chien, Wessel P. Bruinsma, Javier González Hernández, Richard E. Turner:
Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants. ICML 2024 - [i21]Anna Vaughan, Stratis Markou, Will Tebbutt, James Requeima, Wessel P. Bruinsma, Tom R. Andersson, Michael Herzog, Nicholas D. Lane, J. Scott Hosking, Richard E. Turner:
Aardvark Weather: end-to-end data-driven weather forecasting. CoRR abs/2404.00411 (2024) - [i20]Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley, Johannes Brandstetter, Patrick Garvan, Maik Riechert, Jonathan A. Weyn, Haiyu Dong, Anna Vaughan, Jayesh K. Gupta, Kit Thambiratnam, Alex Archibald, Elizabeth Heider, Max Welling, Richard E. Turner, Paris Perdikaris:
Aurora: A Foundation Model of the Atmosphere. CoRR abs/2405.13063 (2024) - [i19]Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben, Antti Honkela, Richard E. Turner:
Noise-Aware Differentially Private Regression via Meta-Learning. CoRR abs/2406.08569 (2024) - [i18]Matthew Ashman, Cristiana Diaconu, Junhyuck Kim, Lakee Sivaraya, Stratis Markou, James Requeima, Wessel P. Bruinsma, Richard E. Turner:
Translation Equivariant Transformer Neural Processes. CoRR abs/2406.12409 (2024) - [i17]Matthew Ashman, Cristiana Diaconu, Adrian Weller, Wessel P. Bruinsma, Richard E. Turner:
Approximately Equivariant Neural Processes. CoRR abs/2406.13488 (2024) - [i16]Wessel P. Bruinsma:
Convolutional Conditional Neural Processes. CoRR abs/2408.09583 (2024) - 2023
- [c11]Wessel P. Bruinsma, Stratis Markou, James Requeima, Andrew Y. K. Foong, Tom R. Andersson, Anna Vaughan, Anthony Buonomo, J. Scott Hosking, Richard E. Turner:
Autoregressive Conditional Neural Processes. ICLR 2023 - [i15]Wessel P. Bruinsma, Stratis Markou, James Requeima, Andrew Y. K. Foong, Tom R. Andersson, Anna Vaughan, Anthony Buonomo, J. Scott Hosking, Richard E. Turner:
Autoregressive Conditional Neural Processes. CoRR abs/2303.14468 (2023) - 2022
- [c10]Wessel P. Bruinsma, Martin Tegner, Richard E. Turner:
Modelling Non-Smooth Signals with Complex Spectral Structure. AISTATS 2022: 5166-5195 - [c9]Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez:
Wide Mean-Field Bayesian Neural Networks Ignore the Data. AISTATS 2022: 5276-5333 - [c8]Stratis Markou, James Requeima, Wessel P. Bruinsma, Anna Vaughan, Richard E. Turner:
Practical Conditional Neural Process Via Tractable Dependent Predictions. ICLR 2022 - [c7]Vidhi Lalchand, Wessel P. Bruinsma, David R. Burt, Carl Edward Rasmussen:
Sparse Gaussian Process Hyperparameters: Optimize or Integrate? NeurIPS 2022 - [i14]Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez:
Wide Mean-Field Bayesian Neural Networks Ignore the Data. CoRR abs/2202.11670 (2022) - [i13]Wessel P. Bruinsma, Martin Tegner, Richard E. Turner:
Modelling Non-Smooth Signals with Complex Spectral Structure. CoRR abs/2203.06997 (2022) - [i12]Stratis Markou, James Requeima, Wessel P. Bruinsma, Anna Vaughan, Richard E. Turner:
Practical Conditional Neural Processes Via Tractable Dependent Predictions. CoRR abs/2203.08775 (2022) - [i11]Andrew Y. K. Foong, Wessel P. Bruinsma, David R. Burt:
A Note on the Chernoff Bound for Random Variables in the Unit Interval. CoRR abs/2205.07880 (2022) - [i10]Ambrish Rawat, James Requeima, Wessel P. Bruinsma, Richard E. Turner:
Challenges and Pitfalls of Bayesian Unlearning. CoRR abs/2207.03227 (2022) - [i9]Vidhi Lalchand, Wessel P. Bruinsma, David R. Burt, Carl E. Rasmussen:
Sparse Gaussian Process Hyperparameters: Optimize or Integrate? CoRR abs/2211.02476 (2022) - [i8]Tom R. Andersson
, Wessel P. Bruinsma, Stratis Markou, James Requeima, Alejandro Coca-Castro, Anna Vaughan, Anna-Louise Ellis, Matthew Lazzara, Daniel C. Jones, J. Scott Hosking, Richard E. Turner:
Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement. CoRR abs/2211.10381 (2022) - 2021
- [c6]Andrew Y. K. Foong, Wessel P. Bruinsma, David R. Burt, Richard E. Turner:
How Tight Can PAC-Bayes be in the Small Data Regime? NeurIPS 2021: 4093-4105 - [i7]Wessel P. Bruinsma, James Requeima, Andrew Y. K. Foong, Jonathan Gordon, Richard E. Turner:
The Gaussian Neural Process. CoRR abs/2101.03606 (2021) - [i6]Andrew Y. K. Foong, Wessel P. Bruinsma, David R. Burt, Richard E. Turner:
How Tight Can PAC-Bayes be in the Small Data Regime? CoRR abs/2106.03542 (2021) - [i5]Stratis Markou, James Requeima, Wessel P. Bruinsma, Richard E. Turner:
Efficient Gaussian Neural Processes for Regression. CoRR abs/2108.09676 (2021) - 2020
- [c5]Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner:
Convolutional Conditional Neural Processes. ICLR 2020 - [c4]Wessel P. Bruinsma, Eric Perim, William Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner:
Scalable Exact Inference in Multi-Output Gaussian Processes. ICML 2020: 1190-1201 - [c3]Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner:
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. NeurIPS 2020 - [i4]Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner:
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. CoRR abs/2007.01332 (2020)
2010 – 2019
- 2019
- [c2]Pavel Berkovich, Eric Perim, Wessel P. Bruinsma:
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models. AABI 2019: 1-14 - [c1]James Requeima, William Tebbutt, Wessel P. Bruinsma, Richard E. Turner:
The Gaussian Process Autoregressive Regression Model (GPAR). AISTATS 2019: 1860-1869 - [i3]Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner:
Convolutional Conditional Neural Processes. CoRR abs/1910.13556 (2019) - [i2]Pavel Berkovich, Eric Perim, Wessel P. Bruinsma:
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models. CoRR abs/1911.01929 (2019) - [i1]Wessel P. Bruinsma, Eric Perim, William Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner:
Scalable Exact Inference in Multi-Output Gaussian Processes. CoRR abs/1911.06287 (2019)
Coauthor Index
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last updated on 2024-09-30 00:57 CEST by the dblp team
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