A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models. - rouyang2017/SISSO
National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data[J]. Geoscience Frontiers, 2021, 12(6): 101248. DOI: 10.1016/j.gsf.2021.101248 Citation: Qigen Lin, Pedro Lima, Stefan Steger, Thomas Glade, Tong Jiang, Jiahui ...
目前CV的研究已经走向大数据、大算力、大模型时代,模型参数量剧增和其所处的黑盒(black-box)状态让我们很难去开展可解释性的研究,也很难去找到一个具体的理论来支持大模型的建模,更多的研究思路还是data-driven的形式。而我近期和一些做认知心理学的同学交流,发现他们在建模一些心理学机理的时候并不会去使用很复杂...
: A data-driven approach to the exploration of spatial-temporal dimensions of conflict. In: Proceedings of the 2Nd ACM SIGSPATIAL workshop on geospatial humanities, geohumanities’18. ACM, New York, NY, USA. pp. 1:1–1:10 Maire M, Yu SX, Perona P (2013) Hierarchical scene annotation ...
港科开设Master of Science in Data-Driven Modeling 2020年：港中深成立成立数据科学学院，随后开设Master...
et al. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics 14, 293 (2013). Article CAS PubMed PubMed Central Google Scholar Tian, Y. et al. ChAMP: updated methylation analysis pipeline for Illumina BeadChips. Bioinformatics 33, 3982–3984 (2017). ...
data-driven and that data facilitate AI advancement. ‘Data Holders’ here means born-digital companies that operate globally. In terms of the literature on BDBM, data holders are vertically integrated. They create and capture value by internalising the whole BD life-cycle from data collection ...
Recent technological advancements are also playing an important role whereby, data-driven insights are interconnected with NATs. In this regard, NATs such as AI and machine learning (ML) are becoming more mainstream with several implications for the development of personalized offerings (Krafft, Laszlo...
(3) The suitability of the methods. We argue that in order to close this gap it is necessary to adopt a model-centric approach to data-driven network analysis, requiring an appropriate level of abstraction to describe the object of study (often not directly observed in the data), and an ...
Shapley A data-driven framework to quantify the value of classifiers in a machine learning ensemble. DAGsHub A platform built on open source tools for data, model and pipeline management. Deepnote A new kind of data science notebook. Jupyter-compatible, with real-time collaboration and running in...