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Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...
High-throughput generation of large and consistent ab initio data combined with advanced machine-learning techniques are enabling the creation of interatomic potentials of near ab initio quality. This capability has the potential of dramatically impacting ...
Amyloidosis refers to a range of medical conditions in which misshapen proteins accumulate in various organs and tissues, forming insoluble fibrils. Cardiac amyloidosis is frequently linked to the buildup of misfolded transthyretin (TTR) or immunoglobulin ...
The dependency on fossil fuels and their impact on the environment is a matter of great concern for the future sustainability of modern society. The development of the "green" technologies which utilize renewable energy sources is now under investigation. ...
Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic d ...
We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised le ...
Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to protein structure and function. They thus open the possibility for generating no ...
The data and scripts used to produce, analyze, and visualize the results of the manuscript Enzyme promiscuous profiles for protein sequence and reaction annotation by Homa MohammadiPeyhani, Anastasia Sveshnikova, Ljubisa Miskovic, and Vassily Hatzimanikati ...
Surrogate deep neural networks (DNNs) can significantly speed up the engineering design process by providing a quick prediction that emulates simulated data. Many previous works have considered improving the accuracy of such models by introducing additiona ...
Medical research and technological advancements are heading towards tailored healthcare approaches that prioritize individual needs, allowing for more accurate diagnoses, more effective treatments, and better patient outcomes overall. One such approach is ...
