16 papers · ranked by Valyu relevance
Ke Shang, Weiyu Chen, Weiduo Liao, Hisao Ishibuchi
—In this letter, we propose HV-Net, a new method for hypervolume approximation in evolutionary multi-objective optimization. The basic idea of HV-Net is to use DeepSets, a deep neural network with permutation invariant property, to approximate the hypervolume of a non-dominated solution set. The input of HV-Net is a…
Ke Shang, Tianye Shu, Hisao Ishibuchi
—Hypervolume contribution is an important concept in evolutionary multi-objective optimization (EMO). It involves in hypervolume-based EMO algorithms and hypervolume subset selection algorithms. Its main drawback is that it is computationally expensive in high-dimensional spaces, which limits its applicability to…
Marcelo F. Rego, Júlio Cesar E.M. Pinto, Luciano P. Cota, Marcone J.F. Souza + 1 more
'Marcone J.F. Souza' 'Mehmet Cunkas'] In many countries, there is an energy pricing policy that varies according to the time-of-use. In this context, it is financially advantageous for the industries to plan their production considering this policy. This article introduces a new bi-objective unrelated parallel machine…
Jaime Carrasco, Fulgencio Lisón, Laura Jiménez, Andrés Weintraub
Methods that estimate the niche of a species by calculating a convex hull or an elliptical envelope have become popular due to their simplicity and interpretation, given Hutchinson’s conception of the niche as an n-dimensional hypervolume. It is well known that convex hulls are sensitive to outliers and do not have the…
Jim Boelrijk, Bernd Ensing, Patrick Forré
Optimizing multiple competing objectives is a common problem across science and industry. The inherent inextricable trade-off between those objectives leads one to the task of exploring their Pareto front. A meaningful quantity for the purpose of the latter is the hypervolume indicator, which is used in Bayesian…
Hao Wang, Kaifeng Yang, Michael Affenzeller, Michael Emmerich
Hypervolume improvement (HVI) is commonly employed in multi-objective Bayesian optimization algorithms to define acquisition functions due to its Pareto-compliant property. Rather than focusing on specific statistical moments of HVI, this work aims to provide the exact expression of HVI's probability distribution for…
Pedro Conceição, Juliano Morimoto
Hutchinson’s niche hypervolume concept has enabled significant progress in our understanding of species’ ecological needs and distributions across environmental gradients. Nevertheless, the properties of Hutchinson’s n-dimensional hypervolumes can be challenging to calculate and several methods have been proposed to…
Diane Espel, Camille Coux, Luis R. Pertierra, Pauline Eymar-Dauphin + 4 more
'Jonas J. Lembrechts' 'David Renault' 'Paulo A. V. Borges' 'Mário Boieiro'] Simple Summary When exposed to gradual stresses such as climate warming, species with high plasticity may develop different growth types (morphotypes) adapted to specific ranges of the temperature spectrum, thereby securing their survival in…
Chuliang Song, Muyang Lu, Joseph R. Bennett, Benjamin Gilbert + 2 more
Beta diversity—the variation among community compositions in a region—is a fundamental measure of biodiversity. Despite a diverse set of measures to quantify beta diversity, most measures have posited that beta diversity is maximized when each community has a single distinct species. However, this assumption overlooks…
Jonas Verhellen
Computer-assisted design of small molecules has experienced a resurgence in academic and industrial interest due to the widespread use of data-driven techniques such as deep generative models. While the ability to generate molecules that fulfil required chemical properties is encouraging, the use of deep learning…
Fernanda S. Caron, David F. R. P. Burslem, Juliano Morimoto
The niche is a fundamental concept in ecology. One way to represent the niche is to use multidimensional geometry known as the Hutchinsonian niche hypervolume. However, hypervolume data are complex and the biological significance of niche hypervolume properties needs to be better understood. Here, we conducted for the…
Jihong Huang, Ruoyun Yu, Runguo Zang
Functional traits play an important role in studying the functional niche in plant communities. However, it remains unclear whether the functional niches of typical forest plant communities in different climatic regions based on functional traits are consistent. Here, we present data for 215 woody species, encompassing…
Andre KY Low, Flore Mekki-Berrada, Aleksandr Ostudin, Jiaxun Xie + 7 more
The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. When solving optimization problems, Bayesian-based optimizers are often…
Jiyizhe Zhang, Daria Semochkina, Naoto Sugisawa, David Woods + 1 more
Multi-objective Bayesian optimization (MOBO) has shown to be a promising tool for reaction development. However, noise is usually unavoidable during experiments and makes it challenging to find reliable solutions. In this study, we focus on finding a set of optimal reaction conditions using multi-objective Euclidian…
Jiyizhe Zhang, Naoto Sugisawa, Kobi Felton, Shinichiro Fuse + 1 more
Amide bond formation is one of the most prevalent reactions in pharmaceutical industry, among which the Schotten-Baumann reaction has attracted attention as a potential green amide formation approach. However, the use of water in the reaction system often causes undesired hydrolysis and can generate a multiphase…
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Zero- to ultralow-field (ZULF) NMR promises chemical sensing with portable devices, but weak thermal polarization and low natural isotopic abundance of heteronuclei limit its sensitivity. Here we combine Signal Amplification by Reversible Exchange (SABRE) and SABRE-relay with in situ ZULF NMR detection, and introduce…