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Found 7 papers, 1 papers with code
Classification of Histology Sections via Multispectral Convolutional Sparse Coding
Image-based classification of histology sections plays an important role in predicting clinical outcomes.
Automatic Group Cohesiveness Detection With Multi-modal Features
The task is to predict the cohesive level for a group of people in images.
Continual Learning Long Short Term Memory
Catastrophic forgetting in neural networks indicates the performance decreasing of deep learning models on previous tasks while learning new tasks.
A Probabilistic Representation for Deep Learning: Delving into The Information Bottleneck Principle
The Information Bottleneck (IB) principle has recently attracted great attention to explaining Deep Neural Networks (DNNs), and the key is to accurately estimate the mutual information between a hidden layer and dataset.
A Probabilistic Representation of DNNs: Bridging Mutual Information and Generalization
However, it is intractable to accurately estimate the MI in DNNs, thus most previous works have to relax the MI bound, which in turn weakens the information theoretic explanation for generalization.
A Black-Box Attack on Optical Character Recognition Systems
models are one of the major concerns with an increasing number of effective adversarial attack methods.
GReAT: A Graph Regularized Adversarial Training Method
GReAT deploys the graph structure of the data into the adversarial training process, resulting in more robust models that better generalize its testing performance and defend against adversarial attacks.
