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Artificialintelligence(AI)isshowingpromiseinearthquakeprediction,challengingthelong-heldbeliefthatitisimpossible.ResearchersattheUniversityofTexas,Austin,havedevelopedanAIalgorithm(算法)thatcorrectlypredicted70%ofearthquakesaweekinadvanceduringatrialinChinaandprovidedaccuratestrengthcalculationsforthepredictedearthquakes.Therese...
在本文中,探讨了提高深度学习建模极端事件以进行时间序列预测的能力。 Extreme Value Loss (EVL) 论文发现深度学习方法的弱点源于传统形式的二次损失函数。为了解决这个问题,论文从极值理论中汲取灵感,开发了一种新的损失函数,称为极值损失(EVL),用于检测未来发生的极端事件。 Memory Network 使用记忆网络来记忆历史记录...
Conformal prediction is a distribution-free method for uncertainty quantification that ensures finite sample guarantee. However, its validity relies on the assumption of data exchangeability. In this talk, I will introduce several conform...
Here, we present our machine learning model developed to predict synergistic drug combinations for the DREAM AstraZeneca-Sanger Drug Combination Prediction Challenge. In order to best encapsulate the biological patterns underlying this synergy, we explored the most predictive and biologically relevant ...
Prediction of functional impact of nsSNP by PANTHER PANTHER predicts the impact of mutation on the protein function. It uses HMM and various alignment method to map the mutation and then produces result. It gives result in the form of probability of damage associated with that SNP and noted as...
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1.Although the orignial author did segmamention in raw dataset, at the tokenization step his model still divide a sentence into chars instead of words. 2. Although from above picture it fits well, when we foucs on clsoe price change, you can see its prediction power is not so appealing....
Artificial intelligence (AI) is showing promise in earthquake prediction, challenging the long-held belief that it is impossible. Researchers at the University of Texas, Austin, have developed an AI algorithm(算法) that correctly predicted 70% of earthquakes a week in advance during a trial in Ch...
Thus, it is not clear yet which social metrics are used in prediction models and what are the results of their use in different contexts. Objective: To identify, characterize, and classify social metrics included in prediction models reported in the literature. Method: We conducted a mapping ...