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08/24/2023
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification
Convolutional neural networks excel in histopathological image classific...
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08/15/2023
A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning
Knowledge Graph Embedding (KGE) has proven to be an effective approach t...
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06/27/2022
Zero Stability Well Predicts Performance of Convolutional Neural Networks
The question of what kind of convolutional neural network (CNN) structur...
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01/19/2022
Decoupling the Depth and Scope of Graph Neural Networks
State-of-the-art Graph Neural Networks (GNNs) have limited scalability w...
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12/03/2021
Residual-Based Adaptive Coefficient and Noise-Immunity ZNN for Perturbed Time-Dependent Quadratic Minimization
The time-dependent quadratic minimization (TDQM) problem appears in many...
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07/09/2021
Activated Gradients for Deep Neural Networks
Deep neural networks often suffer from poor performance or even training...
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12/02/2020
Deep Graph Neural Networks with Shallow Subgraph Samplers
While Graph Neural Networks (GNNs) are powerful models for learning repr...
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10/30/2020
Revisiting Graph Neural Networks for Link Prediction
Graph neural networks (GNNs) have achieved great success in recent years...
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09/14/2020
Deforming the Loss Surface to Affect the Behaviour of the Optimizer
In deep learning, it is usually assumed that the optimization process is...
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07/24/2020
Deforming the Loss Surface
In deep learning, it is usually assumed that the shape of the loss surfa...
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04/25/2017
Introspective Generative Modeling: Decide Discriminatively
We study unsupervised learning by developing introspective generative mo...
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04/25/2017
Introspective Classifier Learning: Empower Generatively
In this paper we propose introspective classifier learning (ICL) that em...
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11/28/2016