Decentralized Deterministic Multi-Agent Reinforcement Learning. - Antoine Grosnit; Desmond Cai; Laura Wynter (CDC, 2021)

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning. - Antoine Grosnit; Rasul Tutunov; Alexandre Max Maraval; Ryan-Rhys Griffiths; Alexander I. Cowen-Rivers; Lin Yang; Lin Zhu; Wenlong Lyu; Zhitang Chen; Jun Wang 012; Jan Peters 001; Haitham Bou-Ammar (CoRR, 2021)

Are We Forgetting about Compositional Optimisers in Bayesian Optimisation? - Antoine Grosnit; Alexander I. Cowen-Rivers; Rasul Tutunov; Ryan-Rhys Griffiths; Jun Wang 012; Haitham Bou-Ammar (J. Mach. Learn. Res., 2021)

BOiLS: Bayesian Optimisation for Logic Synthesis. - Antoine Grosnit; Cédric Malherbe; Rasul Tutunov; Xingchen Wan; Jun Wang 012; Haitham Bou-Ammar (DATE, 2022)

Optimistic Tree Searches for Combinatorial Black-Box Optimization. - Cédric Malherbe; Antoine Grosnit; Rasul Tutunov; Haitham Bou-Ammar; Jun Wang 012 (NeurIPS, 2022)

AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation. - Mohammad Asif Khan 001; Alexander I. Cowen-Rivers; Derrick-Goh-Xin Deik; Antoine Grosnit; Kamil Dreczkowski; Philippe A. Robert; Victor Greiff; Rasul Tutunov; Dany Bou-Ammar; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2022)

Sample-Efficient Optimisation with Probabilistic Transformer Surrogates. - Alexandre Maraval; Matthieu Zimmer; Antoine Grosnit; Rasul Tutunov; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2022)

HEBO: An Empirical Study of Assumptions in Bayesian Optimisation. - Alexander I. Cowen-Rivers; Wenlong Lyu; Rasul Tutunov; Zhi Wang 001; Antoine Grosnit; Ryan-Rhys Griffiths; Alexandre Max Maraval; Jianye Hao; Jun Wang 012; Jan Peters 001; Haitham Bou-Ammar (J. Artif. Intell. Res., 2022)

Lightweight Structural Choices Operator for Technology Mapping. - Antoine Grosnit; Matthieu Zimmer; Rasul Tutunov; Xing Li; Lei Chen 031; Fan Yang; Mingxuan Yuan; Haitham Bou-Ammar (DAC, 2023)

Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization. - Kamil Dreczkowski; Antoine Grosnit; Haitham Bou-Ammar (NeurIPS, 2023)

End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes. - Alexandre Maraval; Matthieu Zimmer; Antoine Grosnit; Haitham Bou-Ammar (NeurIPS, 2023)

Contextual Causal Bayesian Optimisation. - Vahan Arsenyan; Antoine Grosnit; Haitham Bou-Ammar (CoRR, 2023)

Why Can Large Language Models Generate Correct Chain-of-Thoughts? - Rasul Tutunov; Antoine Grosnit; Juliusz Ziomek; Jun Wang 012; Haitham Bou-Ammar (CoRR, 2023)

ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning. - 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; et al. (CoRR, 2024)

ShortCircuit: AlphaZero-Driven Circuit Design. - Dimitrios Tsaras; Antoine Grosnit; Lei Chen 031; Zhiyao Xie; Haitham Bou-Ammar; Mingxuan Yuan (CoRR, 2024)

Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level. - Antoine Grosnit; Alexandre Maraval; James Doran; Giuseppe Paolo; Albert Thomas 001; Refinath Shahul Hameed Nabeezath Beevi; Jonas Gonzalez; Khyati Khandelwal; Ignacio Iacobacci; Abdelhakim Benechehab; Hamza Cherkaoui; Youssef Attia El Hili; et al. (CoRR, 2024)

Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information. - Rasul Tutunov; Antoine Grosnit; Haitham Bou-Ammar (CoRR, 2025)