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07/23/2023
An axiomatized PDE model of deep neural networks
Inspired by the relation between deep neural network (DNN) and partial d...
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09/06/2022
Semi-Supervised Clustering via Dynamic Graph Structure Learning
Most existing semi-supervised graph-based clustering methods exploit the...
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08/30/2022
Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods
Training deep neural networks (DNNs) is an important and challenging opt...
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05/16/2022
A scalable deep learning approach for solving high-dimensional dynamic optimal transport
The dynamic formulation of optimal transport has attracted growing inter...
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04/21/2022
Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach
Collecting paired training data is difficult in practice, but the unpair...
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04/14/2022
Unsupervised Deep Learning Meets Chan-Vese Model
The Chan-Vese (CV) model is a classic region-based method in image segme...
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10/23/2021
AFEC: Active Forgetting of Negative Transfer in Continual Learning
Continual learning aims to learn a sequence of tasks from dynamic data d...
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05/07/2021
Diff-ResNets for Few-shot Learning – an ODE Perspective
Interpreting deep neural networks from the ordinary differential equatio...
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02/09/2021
Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection
The multiple-input multiple-output (MIMO) detection problem, a fundament...
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06/10/2020
Interpolation between Residual and Non-Residual Networks
Although ordinary differential equations (ODEs) provide insights for des...
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05/26/2020
An accelerated method for computing stationary states of multicomponent phase field crystal model
Finding the stationary states of a free energy functional is an essentia...
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02/23/2020
Efficient numerical methods for computing the stationary states of phase field crystal models
Finding the stationary states of a free energy functional is an importan...
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11/28/2019
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Existing domain adaptation methods aim at learning features that can be ...
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11/27/2019
Exploring Frequency Domain Interpretation of Convolutional Neural Networks
Many existing interpretation methods of convolutional neural networks (C...
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09/01/2019
An efficient method for computing stationary states of phase field crystal models
Computing stationary states is an important topic for phase field crysta...
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05/28/2019
Brain-inspired reverse adversarial examples
A human does not have to see all elephants to recognize an animal as an ...
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05/17/2019
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
Convolutional neural networks have been widely deployed in various appli...
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04/23/2019
Wasserstein-Fisher-Rao Document Distance
As a fundamental problem of natural language processing, it is important...
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05/31/2018
