Xiuyuan Cheng
18 papers · 2014–2025 · 7 venues · across top CS/AI venues
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Research topics
Deep Learning
(13)
Machine Learning
(11)
Architectures
(9)
Computer Vision
(7)
Core Methods
(7)
Optimization & Theory
(6)
Mathematics & Optimization
(4)
Processing
(4)
Analysis
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Learning Types Β· Machine Learning
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Models
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Optimization
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Techniques
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Application Areas
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Learning Types Β· Deep Learning
(2)
Keywords
filter decomposition
(5)
convolutional neural network
(4)
model compression
(2)
domain adaptation
(2)
unsupervised learning
(2)
deep learning
(2)
action recognition
(2)
spectral method
(2)
neural network
(2)
non-stationary kernel
(2)
generative model
(2)
graph clustering
(1)
neural tangent kernel
(1)
graph classification
(1)
signal classification
(1)
convex optimization
(1)
image classification
(1)
image restoration
(1)
image-to-image translation
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representation learning
(1)
Papers
Computing high-dimensional optimal transport by flow neural networks
AISTATS 2025
Consistency Posterior Sampling for Diverse Image Synthesis
CVPR 2025
Normalizing flow neural networks by JKO scheme
NeurIPS 2023
Spatio-temporal point processes with deep non-stationary kernels
ICLR 2023
Neural Spectral Marked Point Processes
ICLR 2022
Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters
JMLR 2022
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
AISTATS 2021
Graph Convolution with Low-rank Learnable Local Filters
ICLR 2021
Neural Tangent Kernel Maximum Mean Discrepancy
NeurIPS 2021
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks
NeurIPS 2021
A Dictionary Approach to Domain-Invariant Learning in Deep Networks
NeurIPS 2020
Stochastic Conditional Generative Networks with Basis Decomposition
ICLR 2020
Variational Diffusion Autoencoders with Random Walk Sampling
ECCV 2020
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks
ICLR 2019
DCFNet: Deep Neural Network with Decomposed Convolutional Filters
ICML 2018
Provable Estimation of the Number of Blocks in Block Models
AISTATS 2018
A Deep Learning Approach to Unsupervised Ensemble Learning
ICML 2016
Unsupervised Deep Haar Scattering on Graphs
NeurIPS 2014