Enhancing scientific discoveries in molecular biology with deep generative models
Abstract Generative models provide a well‐established statistical framework for evaluating uncertainty and deriving conclusions from large data sets especially in the presence of noise, sparsity, and bias. Initially developed for computer vision and natural language processing, these models have bee...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Nature
2020-09-01
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| Series: | Molecular Systems Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.15252/msb.20199198 |