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Found 3 papers, 1 papers with code
Survey of Deep Learning Methods for Inverse Problems
In this paper we investigate a variety of deep learning strategies for solving inverse problems.
PathoNet: Deep learning assisted evaluation of Ki-67 and tumor infiltrating lymphocytes (TILs) as prognostic factors in breast cancer; A large dataset and baseline
The nuclear protein Ki-67 and Tumor infiltrating lymphocytes (TILs) have been introduced as prognostic factors in predicting tumor progression and its treatment response.
Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering
Deep generative models are stochastic neural networks capable of learning the distribution of data so as to generate new samples.
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