Search Results for author:
Found 9 papers, 3 papers with code
Regression-free Blind Image Quality Assessment with Content-Distortion Consistency
Finally, quality prediction is obtained by aggregating the subjective scores of the retrieved instances.
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
In this paper, we propose a model-agnostic model-level explanation method for different GNNs that follow the message passing scheme, GNNInterpreter, to explain the high-level decision-making process of the GNN model.
SmartGD: A GAN-Based Graph Drawing Framework for Diverse Aesthetic Goals
There are a few existing methods that have attempted to develop a flexible solution for optimizing different aesthetic aspects measured by different aesthetic criteria.
PrEF: Percolation-based Evolutionary Framework for the diffusion-source-localization problem in large networks
We assume that the state of a number of nodes in a network could be investigated if necessary, and study what configuration of those nodes could facilitate a better solution for the diffusion-source-localization (DSL) problem.
Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery
Therefore, we conjecture that the multimodal and local-global combination strategies can be treated as the guideline of multi-task SSL for drug discovery.
FEDI: Few-shot learning based on Earth Mover's Distance algorithm combined with deep residual network to identify diabetic retinopathy
Diabetic retinopathy(DR) is the main cause of blindness in diabetic patients.
DeepGD: A Deep Learning Framework for Graph Drawing Using GNN
In this paper, we propose a Convolutional Graph Neural Network based deep learning framework, DeepGD, which can draw arbitrary graphs once trained.
A Novel Learnable Dictionary Encoding Layer for End-to-End Language Identification
A novel learnable dictionary encoding layer is proposed in this paper for end-to-end language identification.
Insights into End-to-End Learning Scheme for Language Identification
After comparing with the state-of-the-art GMM i-vector methods, we give insights into CNN, and reveal its role and effect in the whole pipeline.
