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Due to its empirical success on few shot classification and reinforcement learning, meta-learning recently received a lot of interest. Meta-learning leverages data from previous tasks to quickly learn a new task, despite limited data. In particular, model ...
Optimal pharmacokinetic (PK) properties of therapeutic monoclonal antibodies (mAbs) are essential to achieve the desired pharmacological benefits in patients. To accomplish this, we followed an approach comprising structure-based mAb charge engineering in ...
This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...
A new paradigm for data science has emerged, with quantum data, quantum models, and quantum computational devices. This field, called quantum machine learning (QML), aims to achieve a speedup over traditional machine learning for data analysis. However, it ...
Data-driven building energy modeling is an emerging solution to facilitate the implementation of energy-flexible buildings. However, its black-box nature hinders interpretation, including with respect to human-building interaction. This drawback may bring ...
Over the past few decades, the debates have shifted from whether to how Computer Science (CS) should be introduced into formal education. Given the diverse ways to introduce CS into formal education, and the struggles many countries have faced, considerabl ...
Social media has created new opportunities to map cultural ecosystem services (CES) related to biodiversity at large scales. However, using these novel data to understand people's preferences in relation to these CES remains a challenge. To address this, w ...
Planning and execution of voluntary movement depend on the contribution of distinct classes of neurons in primary motor and premotor areas. However, timing and pattern of activation of GABAergic cells during specific motor behaviors remain only partly unde ...
Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...
The invention concerns a single-particle inductively-coupled plasma (ICP) mass spectrometry particle sizing and counting method comprising providing or receiving an intensity-versus-counts histogram of particles detected using an ICP mass spectrometer, the ...