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ORCIDAntoine Grosnit
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2020 – today
- 2024
[i13]Christopher E. Mower, Yuhui Wan, Hongzhan Yu, Antoine Grosnit, Jonas Gonzalez-Billandon, Matthieu Zimmer, Jinlong Wang, Xinyu Zhang, Yao Zhao, Anbang Zhai, Puze Liu, Davide Tateo, Cesar Cadena, Marco Hutter, Jan Peters, Guangjian Tian, Yuzheng Zhuang, Kun Shao, Xingyue Quan, Jianye Hao, Jun Wang, Haitham Bou-Ammar:
ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. CoRR abs/2406.19741 (2024)- [i12]Dimitrios Tsaras, Antoine Grosnit, Lei Chen, Zhiyao Xie, Haitham Bou-Ammar, Mingxuan Yuan:
ShortCircuit: AlphaZero-Driven Circuit Design. CoRR abs/2408.09858 (2024) - [i11]Antoine Grosnit, Alexandre Maraval, James Doran, Giuseppe Paolo, Albert Thomas, Refinath Shahul Hameed Nabeezath Beevi, Jonas Gonzalez, Khyati Khandelwal, Ignacio Iacobacci, Abdelhakim Benechehab, Hamza Cherkaoui, Youssef Attia El Hili, Kun Shao, Jianye Hao, Jun Yao, Balázs Kégl, Haitham Bou-Ammar, Jun Wang:
Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level. CoRR abs/2411.03562 (2024) - 2023
- [c6]Antoine Grosnit, Matthieu Zimmer, Rasul Tutunov, Xing Li, Lei Chen, Fan Yang, Mingxuan Yuan, Haitham Bou-Ammar:
Lightweight Structural Choices Operator for Technology Mapping. DAC 2023: 1-6 - [c5]Kamil Dreczkowski, Antoine Grosnit, Haitham Bou-Ammar:
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization. NeurIPS 2023 - [c4]Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar:
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. NeurIPS 2023 - [i10]Vahan Arsenyan, Antoine Grosnit, Haitham Bou-Ammar:
Contextual Causal Bayesian Optimisation. CoRR abs/2301.12412 (2023) - [i9]Alexandre Maraval, Matthieu Zimmer, Antoine Grosnit, Haitham Bou-Ammar:
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. CoRR abs/2305.15930 (2023) - [i8]Kamil Dreczkowski, Antoine Grosnit, Haitham Bou-Ammar:
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization. CoRR abs/2306.09803 (2023) - [i7]Rasul Tutunov, Antoine Grosnit, Juliusz Ziomek, Jun Wang, Haitham Bou-Ammar:
Why Can Large Language Models Generate Correct Chain-of-Thoughts? CoRR abs/2310.13571 (2023) - 2022
- [j2]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) - [c3]Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou-Ammar:
BOiLS: Bayesian Optimisation for Logic Synthesis. DATE 2022: 1193-1196 - [c2]Cédric Malherbe, Antoine Grosnit, Rasul Tutunov, Haitham Bou-Ammar, Jun Wang:
Optimistic Tree Searches for Combinatorial Black-Box Optimization. NeurIPS 2022 - [i6]Mohammad Asif Khan, Alexander I. Cowen-Rivers, Derrick-Goh-Xin Deik, Antoine Grosnit, Kamil Dreczkowski, Philippe A. Robert, Victor Greiff, Rasul Tutunov, Dany Bou-Ammar, Jun Wang, Haitham Bou-Ammar:
AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. CoRR abs/2201.12570 (2022) - [i5]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
- [j1]Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar:
Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? J. Mach. Learn. Res. 22: 160:1-160:78 (2021) - [c1]Antoine Grosnit, Desmond Cai, Laura Wynter:
Decentralized Deterministic Multi-Agent Reinforcement Learning. CDC 2021: 1548-1553 - [i4]Antoine Grosnit, Desmond Cai, Laura Wynter:
Decentralized Deterministic Multi-Agent Reinforcement Learning. CoRR abs/2102.09745 (2021) - [i3]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) - [i2]Antoine Grosnit, Cédric Malherbe, Rasul Tutunov, Xingchen Wan, Jun Wang, Haitham Bou-Ammar:
BOiLS: Bayesian Optimisation for Logic Synthesis. CoRR abs/2111.06178 (2021) - 2020
- [i1]Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar:
Are we Forgetting about Compositional Optimisers in Bayesian Optimisation? CoRR abs/2012.08240 (2020)
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