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Articles: 2'506'133
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27 April 2024
 
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Results 1 to 20 of 71 for query "Richard E. Turner". (0.01 sec.)

[    1    2    3    4    ]   Next

1.
Multi-disciplinary fairness considerations in machine learning for clinical trials
Isabel Chien; Nina Deliu; Richard E. Turner; Adrian Weller; Sofia S. Villar; Niki Kilbertus;
18 May 2022
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2.
Contextual HyperNetworks for Novel Feature Adaptation
Angus Lamb; Evgeny Saveliev; Yingzhen Li; Sebastian Tschiatschek; Camilla Longden; Simon Woodhead; José Miguel Hernández-Lobato; Richard E. Turner; Pashmina Cameron; Cheng Zhang;
13 Apr 2021
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3.
Scalable Exact Inference in Multi-Output Gaussian Processes
Wessel P. Bruinsma; Eric Perim; Will Tebbutt; J. Scott Hosking; Arno Solin; Richard E. Turner;
14 Nov 2019
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4.
Results and Insights from Diagnostic Questions: The NeurIPS 2020 Education Challenge
Zichao Wang; Angus Lamb; Evgeny Saveliev; Pashmina Cameron; Yordan Zaykov; Jose Miguel Hernandez-Lobato; Richard E. Turner; Richard G. Baraniuk; Craig Barton; Simon Peyton Jones; Simon Woodhead; Cheng Zhang;
8 Apr 2021
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5.
Diagnostic Questions:The NeurIPS 2020 Education Challenge
Zichao Wang; Angus Lamb; Evgeny Saveliev; Pashmina Cameron; Yordan Zaykov; José Miguel Hernández-Lobato; Richard E. Turner; Richard G. Baraniuk; Craig Barton; Simon Peyton Jones; Simon Woodhead; Cheng Zhang;
23 Jul 2020
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6.
Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners
Elre T. Oldewage; John Bronskill; Richard E. Turner;
23 Nov 2022
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7.
Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement
Tom R. Andersson; Wessel P. Bruinsma; Stratis Markou; Daniel C. Jones; J. Scott Hosking; James Requeima; Alejandro Coca-Castro; Anna Vaughan; Anna-Louise Ellis; Matthew Lazzara; Richard E. Turner;
18 Nov 2022
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8.
Ice Core Dating using Probabilistic Programming
Aditya Ravuri; Tom R. Andersson; Ieva Kazlauskaite; Will Tebbutt; Richard E. Turner; J. Scott Hosking; Neil D. Lawrence; Markus Kaiser;
29 Oct 2022
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9.
Differentially private partitioned variational inference
Mikko A. Heikkilä; Matthew Ashman; Siddharth Swaroop; Richard E. Turner; Antti Honkela;
23 Sep 2022
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10.
Kernel Learning for Explainable Climate Science
Vidhi Lalchand; Kenza Tazi; Talay M. Cheema; Richard E. Turner; Scott Hosking;
12 Sep 2022
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11.
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification
Massimiliano Patacchiola; John Bronskill; Aliaksandra Shysheya; Katja Hofmann; Sebastian Nowozin; Richard E. Turner;
20 Jun 2022
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12.
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification
Aliaksandra Shysheya; John Bronskill; Massimiliano Patacchiola; Sebastian Nowozin; Richard E Turner;
17 Jun 2022
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13.
Memory Efficient Meta-Learning with Large Images
John Bronskill; Daniela Massiceti; Massimiliano Patacchiola; Katja Hofmann; Sebastian Nowozin; Richard E. Turner;
2 Jul 2021
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14.
Continual Novelty Detection
Rahaf Aljundi; Daniel Olmeda Reino; Nikolay Chumerin; Richard E. Turner;
24 Jun 2021
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15.
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian Processes
Will Tebbutt; Arno Solin; Richard E. Turner;
18 Jun 2021
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16.
Convolutional conditional neural processes for local climate downscaling
Anna Vaughan; Will Tebbutt; J.Scott Hosking; Richard E. Turner;
20 Jan 2021
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17.
Interpreting Spatially Infinite Generative Models
Chaochao Lu; Richard E. Turner; Yingzhen Li; Nate Kushman;
24 Jul 2020
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18.
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
Andrew Y. K. Foong; Wessel P. Bruinsma; Jonathan Gordon; Yann Dubois; James Requeima; Richard E. Turner;
2 Jul 2020
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19.
Continual Learning with Adaptive Weights (CLAW)
Tameem Adel; Han Zhao; Richard E. Turner;
21 Nov 2019
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20.
Practical Deep Learning with Bayesian Principles
Kazuki Osawa; Siddharth Swaroop; Anirudh Jain; Runa Eschenhagen; Richard E. Turner; Rio Yokota; Mohammad Emtiyaz Khan;
6 Jun 2019
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