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Found 4 papers, 3 papers with code
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation
In this paper, we advocate to revive latent variable modeling, essentially the power of representation learning, in the era of Transformers to enhance controllability without hurting state-of-the-art generation effectiveness.
Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events
Our paper is among the first ones by our knowledge to propose a model and to create datasets for the task of "outline to story".
DeepLung: Deep 3D Dual Path Nets for Automated Pulmonary Nodule Detection and Classification
DeepLung consists of two components, nodule detection (identifying the locations of candidate nodules) and classification (classifying candidate nodules into benign or malignant).
Ranked #5 on
Lung Nodule Classification
on LIDC-IDRI
DeepLung: 3D Deep Convolutional Nets for Automated Pulmonary Nodule Detection and Classification
Considering the 3D nature of lung CT data, two 3D networks are designed for the nodule detection and classification respectively.
Automated Pulmonary Nodule Detection And Classification
Classification
+1
