Shenda Hong
17 papers · 2018–2025 · 7 conferences · across top CS/AI conferences
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Keywords
self-supervised learning
(4)
contrastive learning
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representation learning
(3)
diffusion model
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graph representation learning
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temporal dynamics
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domain adaptation
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medical imaging
(1)
transfer learning
(1)
attention mechanism
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time series prediction
(1)
knowledge distillation
(1)
data augmentation
(1)
multimodal learning
(1)
text-to-image generation
(1)
image synthesis
(1)
structure learning
(1)
time series
(1)
time series forecasting
(1)
semi-supervised learning
(1)
Papers
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
ICLR 2025
Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model
ICLR 2025
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
ICLR 2024
Retrieval-Augmented Diffusion Models for Time Series Forecasting
NIPS 2024
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
ICLR 2024
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
ICLR 2024
Frozen Language Model Helps ECG Zero-Shot Learning
MIDL 2023
Improving Diffusion-Based Image Synthesis with Context Prediction
NIPS 2023
Unsupervised Time-Series Representation Learning with Iterative Bilinear Temporal-Spectral Fusion
ICML 2022
Hypergraph Structure Learning for Hypergraph Neural Networks
IJCAI 2022
Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning
ICML 2022
Intra-Inter Subject Self-Supervised Learning for Multivariate Cardiac Signals
AAAI 2022
TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data
IJCAI 2021
RDPD: Rich Data Helps Poor Data via Imitation
IJCAI 2019
MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals
IJCAI 2019
K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection
IJCAI 2019
Knowledge Guided Multi-instance Multi-label Learning via Neural Networks in Medicines Prediction
ACML 2018