SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

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Despite progress in adversarial training (AT), there is a substantial gap between the topperforming and worst-performing classes in many datasets. For example, on CIFAR10, the accuracies for the best and worst classes are 74% and 23%, respectively. We argu ...

Exploring a wide range of relevant design options from the outset is crucial for every sound conceptual design process. Optimization techniques are generally employed to generate well-performing structural design options. However, focusing only on performa ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

Amino alcohols, cyclopropanes and nitriles are privileged structural motifs found in the scaffold of natural products and bioactive compounds. In addition, they are versatile building blocks in organic chemistry. The development of new and increasingly eff ...

SOMOphilic alkyne vs radical-polar crossover approaches: The full story of the azido-alkynylation of alkenes

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Robust Design of Herringbone Grooved Journal Bearings using Multi-Objective Optimization with Artificial Neural Networks

Stable Nonconvex-Nonconcave Training via Linear Interpolation

Robust Design of Herringbone Grooved Journal Bearings using Multi-Objective Optimization with Artificial Neural Networks

Robust optimization of control parameters for WEC arrays using stochastic methods

Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system

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Genetic Algorithms for the Discovery of Homogeneous Catalysts

Demand-based operations of vehicle sharing systems

Revisiting adversarial training for the worst-performing class

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