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Found 4 papers, 2 papers with code
Camera Bias in a Fine Grained Classification Task
We show that correlations between the camera used to acquire an image and the class label of that image can be exploited by convolutional neural networks (CNN), resulting in a model that "cheats" at an image classification task by recognizing which camera took the image and inferring the class label from the camera.
Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions
Graphs have become a crucial way to represent large, complex and often temporal datasets across a wide range of scientific disciplines.
Social and Information Networks
Phenotypic Profiling of High Throughput Imaging Screens with Generic Deep Convolutional Features
While deep learning has seen many recent applications to drug discovery, most have focused on predicting activity or toxicity directly from chemical structure.
Style Augmentation: Data Augmentation via Style Randomization
In addition to standard classification experiments, we investigate the effect of style augmentation (and data augmentation generally) on domain transfer tasks.
