Research map / Reinforcement learning / Visual and representation RL
End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization (ICLR 2020 · similarity 0.90)
- MALIBO: Meta-learning for Likelihood-free Bayesian Optimization (ICML 2024 · similarity 0.89)
- Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling (ICML 2022 · similarity 0.89)
- PABBO: Preferential Amortized Black-Box Optimization (ICLR 2025 · similarity 0.88)
- BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL (ICLR 2025 · similarity 0.87)
- Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal (NeurIPS 2024 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.