Cover Image

Benchmarking Self-Driving Labs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Adesiji, Adedire D., Wang, Jiashuo, Kuo, Cheng-Shu, Brown, Keith A.
Format:	Preprint
Published:	2025
Subjects:	Computational Physics Materials Science Machine Learning Data Analysis, Statistics and Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Neural Network-Guided Symbolic Regression for Interpretable Descriptor Discovery in Perovskite Catalysts
by: Xian, Yeming, et al.
Published: (2025)

Physics-Informed Tree Search for High-Dimensional Computational Design
by: Banik, Suvo, et al.
Published: (2026)

Rapid optimization in high dimensional space by deep kernel learning augmented genetic algorithms
by: Valleti, Mani, et al.
Published: (2024)

Exploring the Limitations of kNN Noisy Feature Detection and Recovery for Self-Driving Labs
by: Shi, Qiuyu, et al.
Published: (2025)

An information-matching approach to optimal experimental design and active learning
by: Kurniawan, Yonatan, et al.
Published: (2024)

Application of machine learning in grain-related clustering of Laue spots in a polycrystalline energy dispersive Laue pattern
by: Tosson, Amir, et al.
Published: (2024)

Physics-guided impact localisation and force estimation in composite plates with uncertainty quantification
by: Xiao, Dong, et al.
Published: (2025)

Beyond empirical models: Discovering new constitutive laws in solids with graph-based equation discovery
by: Xu, Hao, et al.
Published: (2025)

Autonomous Probe Microscopy with Robust Bag-of-Features Multi-Objective Bayesian Optimization: Pareto-Front Mapping of Nanoscale Structure-Property Trade-Offs
by: Barakati, Kamyar, et al.
Published: (2026)

Numerical Analysis of Damage Evolution in Open Hole CFRP Laminates Modified with Electrospun Self Healing Diels Alder Interleaves
by: Chantzi, Marianna, et al.
Published: (2025)

Enhancing Reconstruction Capability of Wavelet Transform Amorphous Radial Distribution Function via Machine Learning Assisted Parameter Tuning
by: Senjaya, Deriyan, et al.
Published: (2025)

Machine Learning Models for Accurately Predicting Properties of CsPbCl3 Perovskite Quantum Dots
by: Çadırcı, Mehmet Sıddık, et al.
Published: (2024)

Boosting SISSO Performance on Small Sample Datasets by Using Random Forests Prescreening for Complex Feature Selection
by: Jiang, Xiaolin, et al.
Published: (2024)

Securing generative artificial intelligence with parallel magnetic tunnel junction true randomness
by: Bao, Youwei, et al.
Published: (2025)

Training-set-free two-stage deep learning for spectroscopic data de-noising
by: Huang, Dongchen, et al.
Published: (2024)

Solving the inverse problem of X-ray absorption spectroscopy via physics-informed deep learning
by: Zhong, Suyang, et al.
Published: (2026)

Imaging 3D Chemistry at 1 nm Resolution with Fused Multi-Modal Electron Tomography
by: Schwartz, Jonathan, et al.
Published: (2023)

Discovery of stable surfaces with extreme work functions by high-throughput density functional theory and machine learning
by: Schindler, Peter, et al.
Published: (2020)

ViPErLEED package I: Calculation of $I(V)$ curves and structural optimization
by: Kraushofer, Florian, et al.
Published: (2024)

SeeBand: A highly efficient, interactive tool for analyzing electronic transport data
by: Parzer, Michael, et al.
Published: (2024)

ViPErLEED package II: Spot tracking, extraction and processing of I(V) curves
by: Schmid, Michael, et al.
Published: (2024)

Structural Optimization in Tensor LEED Using a Parameter Tree and $R$-Factor Gradients
by: Imre, Alexander M., et al.
Published: (2025)

Basis Function Dependence of Estimation Precision for Synchrotron-Radiation-Based Mössbauer Spectroscopy
by: Shieh, Binsheu, et al.
Published: (2024)

Case Studies of Using the Partial-Structure R1 and the Single-Atom R1 to Assemble Small-Molecule Crystal Structures
by: Zhang, Xiaodong
Published: (2024)

Predicting Solid State Material Platforms for Quantum Technologies
by: Hebnes, Oliver Lerstøl, et al.
Published: (2022)

A rule-free workflow for the automated generation of databases from scientific literature
by: Gilligan, Luke P. J., et al.
Published: (2023)

PATHFINDER: Multi-objective discovery in structural and spectral spaces
by: Barakati, Kamyar, et al.
Published: (2026)

Revealing Local Structures through Machine-Learning- Fused Multimodal Spectroscopy
by: Jia, Haili, et al.
Published: (2025)

Selectivity- and Activity-Aware Catalyst Descriptors for CO$_2$ Hydrogenation on Alloy Nanocatalysts using Machine-Learned Force Fields
by: Pisal, Prajwal, et al.
Published: (2026)

Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later
by: Vadeboncoeur, Arnaud, et al.
Published: (2025)

Is the end of Insight in Sight ?
by: Tucny, Jean-Michel, et al.
Published: (2025)

Scientific machine learning in Hydrology: a unified perspective
by: Adombi, Adoubi Vincent De Paul
Published: (2025)

Data-driven topology design using a deep generative model
by: Yamasaki, Shintaro, et al.
Published: (2020)

Predicting Wind Loads on Container Ships in Harbor Environments through Multi-Fidelity Modeling
by: Fiore, Matilde, et al.
Published: (2026)

Accelerating Hamiltonian Monte Carlo for Bayesian Inference in Neural Networks and Neural Operators
by: Thiagarajan, Ponkrshnan, et al.
Published: (2025)

An exact multiple-time-step variational formulation for the committor and the transition rate
by: Lorpaiboon, Chatipat, et al.
Published: (2025)

Hierarchical geometric deep learning enables scalable analysis of molecular dynamics
by: Pengmei, Zihan, et al.
Published: (2025)

Fast frequency reconstruction using Deep Learning for event recognition in ring laser data
by: Di Somma, Giuseppe, et al.
Published: (2025)

Materials Expert-Artificial Intelligence for Materials Discovery
by: Liu, Yanjun, et al.
Published: (2023)

Estimation of material parameter uncertainties using probabilistic and interval approaches
by: Most, Thomas
Published: (2024)