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Xiaoyu Lu
标题
引用次数
引用次数
年份
Structured variationally auto-encoded optimization
X Lu, J Gonzalez, Z Dai, ND Lawrence
International conference on machine learning, 3267-3275, 2018
662018
Causal Bayesian Optimization
V Aglietti, X Lu, A Paleyes, J González
International Conference on Artificial Intelligence and Statistics, 3155-3164, 2020
572020
Relativistic monte carlo
X Lu, V Perrone, L Hasenclever, YW Teh, S Vollmer
Artificial Intelligence and Statistics, 1236-1245, 2017
482017
Additive Gaussian Processes Revisited
X Lu, A Boukouvalas, J Hensman
International Conference on Machine Learning, 14358-14383, 2022
272022
Inference trees: Adaptive inference with exploration
T Rainforth, Y Zhou, X Lu, YW Teh, F Wood, H Yang, JW van de Meent
arXiv preprint arXiv:1806.09550, 2018
142018
On exploration, exploitation and learning in adaptive importance sampling
X Lu, T Rainforth, Y Zhou, JW van de Meent, YW Teh
arXiv preprint arXiv:1810.13296, 2018
102018
Factoredrl: Leveraging factored graphs for deep reinforcement learning
B Balaji, P Christodoulou, X Lu, B Jeon, J Bell-Masterson
52020
Collaborative filtering with side information: a gaussian process perspective
H Kim, X Lu, S Flaxman, YW Teh
arXiv preprint arXiv:1605.07025, 2016
52016
Tucker gaussian process for regression and collaborative filtering
H Kim, X Lu, S Flaxman, YW Teh
arXiv preprint arXiv:1605.07025, 2016
22016
Structure mapping for transferability of causal models
P Pruthi, J González, X Lu, M Fiterau
arXiv preprint arXiv:2007.09445, 2020
12020
Trajectory VAE for multi-modal imitation
X Lu, J Stuehmer, K Hofmann
12018
Explainable Attribution using Additive Gaussian Processes
X Lu, A Boukouvalas, J Hensman
Sixth Symposium on Advances in Approximate Bayesian Inference-Non Archival Track, 2024
2024
Daisee: Adaptive Importance Sampling by Balancing Exploration and Exploitation
X Lu, T Rainforth, YW Teh
Scandinavian Journal of Statistics, 2023
2023
Modelling, inference and optimization in probabilistic machine learning
X Lu
University of Oxford, 2018
2018
Probabilistic Optimization with Latent Search for Automatic Model Selection
X Lu, J González, Z Dai, ND Lawrence
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