Results 81 to 90 of about 4,909,083 (351)

Data-efficient optimization of thermally-activated polymer actuators through machine learning

Materials & Design
For applications in soft robotics and smart textiles, thermally-activated, twisted, and coiled polymer actuators can offer high mechanical actuation with proper optimization of their processing conditions. However, optimization is often aggravated by the
Yuhao Zhang, Maija Vaara, Azin Alesafar, Duc Bach Nguyen, Pedro Silva, Laura Koskelo, Jussi Ristolainen, Matthias Stosiek, Joakim Löfgren, Jaana Vapaavuori, Patrick Rinke   +10 more
doaj   +1 more source

Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces [PDF]

, 2014
In practical Bayesian optimization, we must often search over structures with differing numbers of parameters. For instance, we may wish to search over neural network architectures with an unknown number of layers. To relate performance data gathered for
Duvenaud, David, Hutter, Frank, Osborne, Michael A., Snoek, Jasper, Swersky, Kevin   +4 more
core  

Artificial Intelligence as the Next Visionary in Liquid Crystal Research

Advanced Functional Materials, EarlyView.
The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam, Ouassim L'Karkouri, Danqing Liu   +2 more
wiley   +1 more source

Causal Bayesian Optimization

, 2020
This paper studies the problem of globally optimizing a variable of interest that is part of a causal model in which a sequence of interventions can be performed. This problem arises in biology, operational research, communications and, more generally, in all fields where the goal is to optimize an output metric of a system of interconnected nodes. Our
Aglietti, Virginia, Lu, Xiaoyu, Paleyes, Andrei, González, Javier   +3 more
openaire   +2 more sources

Precise Control of Drug Release in Machine Learning‐Designed Antibody‐Eluting Implants for Postoperative Scarring Inhibition in Glaucoma

Advanced Healthcare Materials, EarlyView.
We developed a micro‐sized, biocompatible implant for postoperative sustained delivery of anti‐fibrotic antibodies in glaucoma surgery. Machine learning‐guided optimization of polymer composition, implant geometry, and porosity enabled precise control of drug release.
Mengqi Qin, Wenbing Jiang, Kai Xin Thong, Zeynep Ulker, Brihitejas Patel, Cynthia Yu‐Wai‐Man   +5 more
wiley   +1 more source

Dynamic Control of Explore/Exploit Trade-Off In Bayesian Optimization

, 2018
Bayesian optimization offers the possibility of optimizing black-box operations not accessible through traditional techniques. The success of Bayesian optimization methods such as Expected Improvement (EI) are significantly affected by the degree of ...
Bobak Shahriari, DR Jones, E Vazquez, F Pedregosa, HJ Kushner, J Bergstra, M Lisicki, N Srivastava, RM Neal   +8 more
core   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Multi-Objective BiLevel Optimization by Bayesian Optimization

Algorithms
In a multi-objective optimization problem, a decision maker has more than one objective to optimize. In a bilevel optimization problem, there are the following two decision-makers in a hierarchy: a leader who makes the first decision and a follower who ...
Vedat Dogan, Steven Prestwich
doaj   +1 more source

Active Learning‐Guided Accelerated Discovery of Ultra‐Efficient High‐Entropy Thermoelectrics

Advanced Materials, EarlyView.
An active learning framework is introduced for the accelerated discovery of high‐entropy chalcogenides with superior thermoelectric performance. Only 80 targeted syntheses, selected from 16206 possible combinations, led to three high‐performance compositions, demonstrating the remarkable efficiency of data‐driven guidance in experimental materials ...
Hanhwi Jang, Wooseok Lee, Hwa‐Jung Kim, Sohyang Cha, Hosun Shin, Won Bo Lee, Min‐Wook Oh, Yeon Sik Jung, YongJoo Kim   +8 more
wiley   +1 more source

Bayesian Optimization with Unknown Constraints [PDF]

, 2014
Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions. Many real-world optimization problems of interest also have constraints which are unknown a priori.
Adams, Ryan P., Gelbart, Michael A., Snoek, Jasper   +2 more
core