Guangyong Chen
28 papers · 2015–2026 · 11 venues · across top CS/AI venues
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Venues
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Machine Learning
(18)
Deep Learning
(13)
Learning Types Β· Machine Learning
(11)
Artificial Intelligence
(9)
Computer Vision
(8)
Architectures
(7)
Core AI
(6)
Core Methods
(6)
Learning Types Β· Deep Learning
(6)
Models
(5)
Reinforcement Learning
(4)
Methods
(4)
Optimization & Theory
(4)
Application Areas
(3)
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(3)
Keywords
multi-agent reinforcement learning
(3)
data augmentation
(3)
label noise
(3)
graph neural network
(3)
catastrophic forgetting
(2)
class-conditional noise
(2)
diffusion model
(2)
point cloud
(2)
evidential deep learning
(2)
text-to-image generation
(2)
bayesian nonparametrics
(1)
few-shot learning
(1)
feature learning
(1)
model selection
(1)
continual learning
(1)
representation learning
(1)
multi-task learning
(1)
graph learning
(1)
semi-supervised learning
(1)
contrastive learning
(1)
Papers
Unifying Multi-View Knowledge for Graph Learning via Model Collaboration
AAAI 2026
MagicTailor: Component-Controllable Personalization in Text-to-Image Diffusion Models
IJCAI 2025
MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding
AAAI 2025
Scene Graph Guided Generation: Enable Accurate Relations Generation in Text-to-Image Models via Textural Rectification
ICCV 2025
ANEDL: Adaptive Negative Evidential Deep Learning for Open-Set Semi-supervised Learning
AAAI 2024
DPPMask: Masked Image Modeling With Determinantal Point Processes
WACV 2024
DR-Label: Label Deconstruction and Reconstruction of GNN Models for Catalysis Systems
AAAI 2024
PointPatchMix: Point Cloud Mixing with Patch Scoring
AAAI 2024
Sample-Efficient Multiagent Reinforcement Learning with Reset Replay
ICML 2024
Text-Anchored Score Composition: Tackling Condition Misalignment in Text-to-Image Diffusion Models
ECCV 2024
RepMode: Learning to Re-Parameterize Diverse Experts for Subcellular Structure Prediction
CVPR 2023
Traj-MAE: Masked Autoencoders for Trajectory Prediction
ICCV 2023
Uncertainty Estimation by Fisher Information-based Evidential Deep Learning
ICML 2023
Acknowledging the Unknown for Multi-Label Learning with Single Positive Labels
ECCV 2022
Explore More Guidance: A Task-aware Instruction Network for Sign Language Translation Enhanced with Data Augmentation
NAACL 2022
G-MAP: General Memory-Augmented Pre-trained Language Model for Domain Tasks
EMNLP 2022
Transformer-based Working Memory for Multiagent Reinforcement Learning with Action Parsing
NeurIPS 2022
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise
AAAI 2021
Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning
NeurIPS 2021
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction
AAAI 2021
Noise against noise: stochastic label noise helps combat inherent label noise
ICLR 2021
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels
AAAI 2021
Q-value Path Decomposition for Deep Multiagent Reinforcement Learning
ICML 2020
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
ICML 2019
Cascaded Feature Network for Semantic Segmentation of RGB-D Images
ICCV 2017
Learning to Aggregate Ordinal Labels by Maximizing Separating Width
ICML 2017
From Noise Modeling to Blind Image Denoising
CVPR 2016
An Efficient Statistical Method for Image Noise Level Estimation
ICCV 2015