Antoine Grosnit

According to our database1, Antoine Grosnit authored at least 13 papers between 2021 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023
Why Can Large Language Models Generate Correct Chain-of-Thoughts?
CoRR, 2023

Contextual Causal Bayesian Optimisation.
CoRR, 2023

End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Lightweight Structural Choices Operator for Technology Mapping.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022
HEBO: An Empirical Study of Assumptions in Bayesian Optimisation.
J. Artif. Intell. Res., 2022

Sample-Efficient Optimisation with Probabilistic Transformer Surrogates.
CoRR, 2022

AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisation.
CoRR, 2022

Optimistic Tree Searches for Combinatorial Black-Box Optimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BOiLS: Bayesian Optimisation for Logic Synthesis.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022

2021
Are We Forgetting about Compositional Optimisers in Bayesian Optimisation?
J. Mach. Learn. Res., 2021

High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learning.
CoRR, 2021

Decentralized Deterministic Multi-Agent Reinforcement Learning.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021


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