Cover Image

Meta-learning for sample-efficient Bayesian optimisation of fed-batch processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Langdon, Becky, Patrón, Gabriel D., Kappatou, Chrysoula D., Lee, Robert M., Shafei, Behrang, Qing, Jixiang, Misener, Ruth, van der Wilk, Mark, Tsay, Calvin
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

System-Aware Neural ODE Processes for Few-Shot Bayesian Optimization
by: Qing, Jixiang, et al.
Published: (2024)

BoGrape: Bayesian optimization over graphs with shortest-path encoded
by: Xie, Yilin, et al.
Published: (2025)

Transition Constrained Bayesian Optimization via Markov Decision Processes
by: Folch, Jose Pablo, et al.
Published: (2024)

Global optimization of graph acquisition functions for neural architecture search
by: Xie, Yilin, et al.
Published: (2025)

Weighted-Sum of Gaussian Process Latent Variable Models
by: Odgers, James, et al.
Published: (2024)

P-split formulations: A class of intermediate formulations between big-M and convex hull for disjunctive constraints
by: Kronqvist, Jan, et al.
Published: (2022)

BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
by: Boyne, Toby, et al.
Published: (2025)

Bayesian optimization as a flexible and efficient design framework for sustainable process systems
by: Paulson, Joel A., et al.
Published: (2024)

Multi-objective optimisation via the R2 utilities
by: Tu, Ben, et al.
Published: (2023)

Scalarisation-based risk concepts for robust multi-objective optimisation
by: Tu, Ben, et al.
Published: (2024)

Transfer learning Bayesian optimization for competitor DNA molecule design for use in diagnostic assays
by: Ruby Sedgwick, et al.
Published: (2024)

BoFire: Bayesian Optimization Framework Intended for Real Experiments
by: Dürholt, Johannes P., et al.
Published: (2024)

The Catechol Benchmark: Time-series Solvent Selection Data for Few-shot Machine Learning
by: Boyne, Toby, et al.
Published: (2025)

Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic Assays
by: Sedgwick, Ruby, et al.
Published: (2024)

Control and optimisation of irreversible processes in non-equilibrium systems
by: Castro, Antonio Patrón
Published: (2025)

Relaxation-Informed Training of Neural Network Surrogate Models
by: Tsay, Calvin
Published: (2026)

Random Pareto front surfaces
by: Tu, Ben, et al.
Published: (2024)

A Meta-Learning Approach to Bayesian Causal Discovery
by: Dhir, Anish, et al.
Published: (2024)

Training Neural ODEs Using Fully Discretized Simultaneous Optimization
by: Shapovalova, Mariia, et al.
Published: (2025)

Scaling Mixed-Integer Programming for Certification of Neural Network Controllers Using Bounds Tightening
by: Sosnin, Philip, et al.
Published: (2024)

Beyond adjacency: Graph encoding with reachability and shortest paths
by: Zhang, Shiqiang, et al.
Published: (2025)

EARL-BO: Reinforcement Learning for Multi-Step Lookahead, High-Dimensional Bayesian Optimization
by: Cheon, Mujin, et al.
Published: (2024)

A Quantile Neural Network Framework for Two-stage Stochastic Optimization
by: Alcántara, Antonio, et al.
Published: (2024)

Bivariate Causal Discovery using Bayesian Model Selection
by: Dhir, Anish, et al.
Published: (2023)

Robust optimal iterative learning control for constrained batch processes with nonuniform batch lengths
by: Jian Ding, et al.
Published: (2025)

TS-RSR: A provably efficient approach for batch Bayesian Optimization
by: Ren, Zhaolin, et al.
Published: (2024)

An exploration for higher efficiency in multi objective optimisation with reinforcement learning
by: Aydin, Mehmet Emin
Published: (2025)

Bayesian optimisation for Bayesian evidence (BOBE) -- a fast and efficient likelihood emulator for model selection
by: Cohen, Nathan, et al.
Published: (2026)

An efficient frequency-independent numerical method for computing the far-field pattern induced by polygonal obstacles
by: Gibbs, A., et al.
Published: (2023)

Results from batch experiments
by: Kaufmann-Knoke, Ruth
Published: (2017)

Characterization of apoptosis in fed‐batch cultures highlights the impact of timely process intervention on improving recombinant protein productivity
by: Misaal Patel, et al.
Published: (2026)

Squalene production from biodiesel‐derived crude glycerol as the substrate by Pichia pastoris in batch and fed‐batch systems
by: R. Srivatsan, et al.
Published: (2026)

Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy
by: Sosnin, Philip, et al.
Published: (2025)

When Deep Learning Meets Polyhedral Theory: A Survey
by: Huchette, Joey, et al.
Published: (2023)

A machine learning‐based approach for improving plasmid DNA production in Escherichia coli fed‐batch fermentations
by: Zhixian Xu, et al.
Published: (2024)

Verifying message-passing neural networks via topology-based bounds tightening
by: Hojny, Christopher, et al.
Published: (2024)

Simulation Based Bayesian Optimization
by: Naveiro, Roi, et al.
Published: (2024)

Using lateral dispersion to optimise microfluidic trap array efficiency
by: Ruyssen, Nicolas, et al.
Published: (2024)

The relative value of interventional and observational samples in Bayesian Causal Linear Gaussian Models
by: Lungu, Valentinian, et al.
Published: (2026)

Fault diagnosis of batch processes for small samples based on contrastive learning
by: Jingyun Xu, et al.
Published: (2025)