{"total":46,"rows":[{"id":"2310.20708","title":"Unexpected Improvements to Expected Improvement for Bayesian Optimization","created":"2023-10-31","cited_by_count":149,"area":null},{"id":"2304.05341","title":"Bayesian Optimization of Catalysis With In-Context Learning","created":"2023-04-11","cited_by_count":22,"area":null},{"id":"2111.14786","title":"Autonomous optimization of nonaqueous battery electrolytes via robotic experimentation and machine learning","created":"2021-11-23","cited_by_count":16,"area":null},{"id":"2302.01511","title":"Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds","created":"2023-02-03","cited_by_count":16,"area":null},{"id":"2208.13771","title":"Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization (ZoMBI)","created":"2022-08-26","cited_by_count":14,"area":null},{"id":"2204.05838","title":"Benchmarking Active Learning Strategies for Materials Optimization and Discovery","created":"2022-04-12","cited_by_count":11,"area":null},{"id":"2206.14917","title":"Towards out of distribution generalization for problems in mechanics","created":"2022-06-29","cited_by_count":11,"area":null},{"id":"2106.04618","title":"EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions","created":"2021-06-08","cited_by_count":9,"area":null},{"id":"2110.01387","title":"Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing","created":"2021-10-01","cited_by_count":8,"area":null},{"id":"2207.04994","title":"Uncertainty-Aware Mixed-Variable Machine Learning for Materials Design","created":"2022-07-11","cited_by_count":6,"area":null},{"id":"2112.00600","title":"Towards Futuristic Autonomous Experimentation--A Surprise-Reacting Sequential Experiment Policy","created":"2021-12-01","cited_by_count":4,"area":null},{"id":"2409.00979","title":"Regret Analysis for Randomized Gaussian Process Upper Confidence Bound","created":"2024-09-02","cited_by_count":4,"area":null},{"id":"2306.04343","title":"Bayesian Optimisation Against Climate Change: Applications and Benchmarks","created":"2023-06-07","cited_by_count":3,"area":null},{"id":"2311.09591","title":"Accelerating material discovery with a threshold-driven hybrid acquisition policy-based Bayesian optimization","created":"2023-11-16","cited_by_count":3,"area":null},{"id":"2511.19730","title":"Training-Free Active Learning Framework in Materials Science with Large Language Models","created":"2025-11-24","cited_by_count":3,"area":null},{"id":"2603.04692","title":"Engineering Regression Without Real-Data Training: Domain Adaptation for Tabular Foundation Models Using Multi-Dataset Embeddings","created":"2026-03-05","cited_by_count":3,"area":null},{"id":"2504.13344","title":"Adaptive AI decision interface for autonomous electronic material discovery","created":"2025-04-17","cited_by_count":2,"area":null},{"id":"2506.19613","title":"Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI","created":"2025-06-24","cited_by_count":2,"area":null},{"id":"2512.01080","title":"Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scores","created":"2025-11-30","cited_by_count":2,"area":null},{"id":"2604.09417","title":"Do We Really Need to Approach the Entire Pareto Front in Many-Objective Bayesian Optimisation?","created":"2026-04-10","cited_by_count":2,"area":null},{"id":"2605.06187","title":"In-Context Black-Box Optimization with Unreliable Feedback","created":"2026-05-07","cited_by_count":2,"area":null},{"id":"2608.00641","title":"DASH: Decoupled Adaptive Surrogate - Acquisition Harness for Automated Bayesian Optimization","created":"2026-08-01","cited_by_count":2,"area":null},{"id":"2312.12633","title":"Long-run Behaviour of Multi-fidelity Bayesian Optimisation","created":"2023-12-19","cited_by_count":1,"area":null},{"id":"2504.08874","title":"Distilling and exploiting quantitative insights from Large Language Models for enhanced Bayesian optimization of chemical reactions","created":"2025-04-11","cited_by_count":1,"area":null},{"id":"2505.06519","title":"Interpretable SHAP-bounded Bayesian Optimization for Underwater Acoustic Metamaterial Coating Design","created":"2025-05-10","cited_by_count":1,"area":null},{"id":"2506.05999","title":"Machine learning for in-situ composition mapping in a self-driving magnetron sputtering system","created":"2025-06-06","cited_by_count":1,"area":null},{"id":"2508.10642","title":"A Guide to Bayesian Optimization in Bioprocess Engineering","created":"2025-08-14","cited_by_count":1,"area":null},{"id":"2603.12567","title":"Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discovery","created":"2026-03-13","cited_by_count":1,"area":null},{"id":"2605.17000","title":"BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks","created":"2026-05-16","cited_by_count":1,"area":null},{"id":"2110.03923","title":"Opportunities for Machine Learning to Accelerate Halide Perovskite Commercialization and Scale-Up","created":"2021-10-08","cited_by_count":0,"area":null},{"id":"2208.07612","title":"Rapid Discovery of Graphene Nanocrystals Using DFT and Bayesian Optimization with Neural Network Kernel","created":"2022-08-16","cited_by_count":0,"area":null},{"id":"2405.03092","title":"Bayesian optimization for stable properties amid processing fluctuations in sputter deposition","created":"2024-05-06","cited_by_count":0,"area":null},{"id":"2406.12661","title":"SCORE: A 1D Reparameterization Technique to Break Bayesian Optimization's Curse of Dimensionality","created":"2024-06-18","cited_by_count":0,"area":null},{"id":"2503.21095","title":"Confidence Adjusted Surprise Measure for Active Resourceful Trials (CA-SMART): A Data-driven Active Learning Framework for Accelerating Material Discovery under Resource Constraints","created":"2025-03-27","cited_by_count":0,"area":null},{"id":"2504.03943","title":"Multi-Variable Batch Bayesian Optimization in Materials Research: Synthetic Data Analysis of Noise Sensitivity and Problem Landscape Effects","created":"2025-04-04","cited_by_count":0,"area":null},{"id":"2505.17393","title":"CatBOX: A Categorical-Continuous Bayesian Optimization with Spectral Mixture Kernels for Accelerated Catalysis Experiments","created":"2025-05-23","cited_by_count":0,"area":null},{"id":"2512.07868","title":"Bayesian Optimization for Function-Valued Responses under Min-Max Criteria","created":"2025-11-26","cited_by_count":0,"area":null},{"id":"2601.05946","title":"A Critical Examination of Active Learning Workflows in Materials Science","created":"2026-01-09","cited_by_count":0,"area":null},{"id":"2601.08185","title":"Autonomous Materials Exploration by Integrating Automated Phase Identification and AI-Assisted Human Reasoning","created":"2026-01-13","cited_by_count":0,"area":null},{"id":"2602.10392","title":"Tensor Methods: A Unified and Interpretable Approach for Material Design","created":"2026-02-11","cited_by_count":0,"area":null},{"id":"2605.00855","title":"An Efficient Spatial Branch-and-Bound Algorithm for Global Optimization of Gaussian Process Posterior Mean Functions","created":"2026-04-21","cited_by_count":0,"area":null},{"id":"2605.20242","title":"LEAP: A closed-loop framework for perovskite precursor additive discovery","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2606.01457","title":"Transferring Information Across Interventions in Causal Bayesian Optimization","created":"2026-05-31","cited_by_count":0,"area":null},{"id":"2607.10669","title":"tidyHEBO: Improving the Robustness of Heteroskedastic Evolutionary Bayesian Optimization","created":"2026-07-12","cited_by_count":0,"area":null},{"id":"2607.17091","title":"ThRIve: Thermally Robust CNN Inference via Low-Rank Adaptation in Heterogeneous PIM Architectures","created":"2026-07-19","cited_by_count":0,"area":null},{"id":"2608.04651","title":"Active Learning Guided Design Space Refinement for Scalable Multi-Objective Bayesian Optimization in Materials Discovery","created":"2026-08-05","cited_by_count":0,"area":null}],"next_cursor":null}