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Alexandre Maraval

Alexandre Max Maraval

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2020 – today

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2023
[c1]
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  - conf/nips/MaravalZGB23
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Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar:
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. NeurIPS 2023
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  - journals/corr/abs-2305-15930
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Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar:
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. CoRR abs/2305.15930 (2023)
2022
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  - journals/jair/Cowen-RiversLTW22
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Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov, Zhi Wang, Antoine Grosnit, Ryan-Rhys Griffiths, Alexandre Max Maraval, Jianye Hao, Jun Wang, Jan Peters, Haitham Bou-Ammar:
HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. J. Artif. Intell. Res. 74: 1269-1349 (2022)
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  - journals/corr/abs-2205-13902
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Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Rasul Tutunov, Jun Wang, Haitham Bou-Ammar:
Sample-Efficient Optimisation with Probabilistic Transformer Surrogates. CoRR abs/2205.13902 (2022)
2021
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  - journals/corr/abs-2101-06070
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Vincent Moens, Hang Ren, Alexandre Maraval, Rasul Tutunov, Jun Wang, Haitham Ammar:
Efficient Semi-Implicit Variational Inference. CoRR abs/2101.06070 (2021)
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  - journals/corr/abs-2106-03609
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Antoine Grosnit, Rasul Tutunov, Alexandre Max Maraval, Ryan-Rhys Griffiths, Alexander I. Cowen-Rivers, Lin Yang, Lin Zhu, Wenlong Lyu, Zhitang Chen, Jun Wang, Jan Peters, Haitham Bou-Ammar:
High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. CoRR abs/2106.03609 (2021)

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