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In this chapter, we discuss the application of deep learning techniques to input data that exhibit a graph structure. We consider both the case in which the input is a single, huge graph (e.g., a social network), where we are interested in predicting the properties of single nodes (e....
•Wikipedia on “Deep Learning” around October 2013. Definition 5: •Deep learning (deep structured learning or hierarchical learning) is a set of algorithms in machine learning that attempt to model high-level ions in data by using model architectures composed of multiple non-linear ...
Computational protein design with data-driven approaches: Recent developments and perspectives Haiyan Liu, Quan Chen WIREs Comput Mol Sci. 2022. e1646 Understanding by design: Implementing deep learning from protein structure prediction to protein design Gao, Yuanxu, Jiangshan Zhan, and Albert CH Yu ...
Computational methods for predicting protein function are of great significance in understanding biological mechanisms and treating complex diseases. However, existing computational approaches of protein function prediction lack interpretability, making
Learning Deep Structured Semantic Models for Web Search using Clickthrough Data Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, Larry Heck October 2013 Published by ACM International Conference on Information and Knowledge Management (CIKM) ...
Our study aimed to develop and validate a deep learning-based model with dual interaction modules to accurately predict the long-term conversion from MCI to AD using sMRI, clinical characteristics, and genetic polymorphism data. We also assessed model robustness across different clinical centers and ...
Deep Learning Book Chinese Translation. Contribute to MagnetStone/deeplearningbook-chinese development by creating an account on GitHub.
we process them with a method similar to cross-information learning. By fine-tuning on PCdes data, KV-PLM can achieve cross retrieval between substances and property descriptions. We propose a new task CHEMIchoice to evaluate the reading ability on SMILES strings and natural language and also th...
Moreover, models with higher complexity require the specification of a large number of parameters whose values can be difficult to infer from limited data. There has been a recent gain of interest towards using machine learning to address the issue of the often-limiting complexity of mechanistic ...