:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Liang, Tao, Xiang, Liu, Qiang, Wu, Shu
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2402.07225
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection
by: Tao, Xiang, et al.
Published: (2024)

Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders
by: Liu, Chuang, et al.
Published: (2024)

Bi-Level Graph Structure Learning for Next POI Recommendation
by: Wang, Liang, et al.
Published: (2024)

Hi-GMAE: Hierarchical Graph Masked Autoencoders
by: Liu, Chuang, et al.
Published: (2024)

Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules
by: Liu, Zhiyuan, et al.
Published: (2023)

DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
by: Sun, Xin, et al.
Published: (2024)

Graph Generative Models Evaluation with Masked Autoencoder
by: Wang, Chengen, et al.
Published: (2025)

Masked BRep Autoencoder via Hierarchical Graph Transformer
by: Li, Yifei, et al.
Published: (2026)

Neuro-BERT: Rethinking Masked Autoencoding for Self-supervised Neurological Pretraining
by: Wu, Di, et al.
Published: (2022)

Rethinking The Uniformity Metric in Self-Supervised Learning
by: Fang, Xianghong, et al.
Published: (2024)

Route Sparse Autoencoder to Interpret Large Language Models
by: Shi, Wei, et al.
Published: (2025)

Masked Autoencoders Are Effective Tokenizers for Diffusion Models
by: Chen, Hao, et al.
Published: (2025)

UGMAE: A Unified Framework for Graph Masked Autoencoders
by: Tian, Yijun, et al.
Published: (2024)

Rethinking Generalization in Graph Neural Networks: A Structural Complexity Perspective
by: Wang, Peiyao, et al.
Published: (2026)

SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
by: Liang, Feng, et al.
Published: (2022)

Enhancing LLM Steering through Sparse Autoencoder-Based Vector Refinement
by: Wang, Anyi, et al.
Published: (2025)

Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction
by: Wang, Liang, et al.
Published: (2024)

Masked Graph Autoencoder with Non-discrete Bandwidths
by: Zhao, Ziwen, et al.
Published: (2024)

Revisiting Graph Autoencoders as Implicit Contrastive Learners
by: Li, Jintang, et al.
Published: (2024)

Ensemble Visualization With Variational Autoencoder
by: Wu, Cenyang, et al.
Published: (2025)

Graffe: Graph Representation Learning via Diffusion Probabilistic Models
by: Chen, Dingshuo, et al.
Published: (2025)

Detecting Generative Parroting through Overfitting Masked Autoencoders
by: Taghanaki, Saeid Asgari, et al.
Published: (2024)

Learnable Chernoff Baselines for Inference-Time Alignment
by: Madhow, Sunil, et al.
Published: (2026)

TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
by: Cheng, Mingyue, et al.
Published: (2023)

SARMAE: Masked Autoencoder for SAR Representation Learning
by: Liu, Danxu, et al.
Published: (2025)

T-GAE: Transferable Graph Autoencoder for Network Alignment
by: He, Jiashu, et al.
Published: (2023)

ExLM: Rethinking the Impact of [MASK] Tokens in Masked Language Models
by: Zheng, Kangjie, et al.
Published: (2025)

Mask and Restore: Blind Backdoor Defense at Test Time with Masked Autoencoder
by: Sun, Tao, et al.
Published: (2023)

Masked Autoencoders are PDE Learners
by: Zhou, Anthony, et al.
Published: (2024)

Masked Graph Learning with Recurrent Alignment for Multimodal Emotion Recognition in Conversation
by: Meng, Tao, et al.
Published: (2024)

3D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding
by: Wu, Chang, et al.
Published: (2025)

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach
by: Zhu, Yinlin, et al.
Published: (2026)

Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
by: Xiang, Xiao, et al.
Published: (2026)

Text-Guided Molecule Generation with Diffusion Language Model
by: Gong, Haisong, et al.
Published: (2024)

Rethinking Graph Generalization through the Lens of Sharpness-Aware Minimization
by: Qiu, Yang, et al.
Published: (2026)

Diffusion Models for Molecules: A Survey of Methods and Tasks
by: Wang, Liang, et al.
Published: (2025)

Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
by: Yang, Shenzhi, et al.
Published: (2025)

SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
by: Yan, Qi, et al.
Published: (2023)

Likelihood-Free Variational Autoencoders
by: Xu, Chen, et al.
Published: (2025)

MOMA: Masked Orthogonal Matrix Alignment for Zero-Additional-Parameter Model Merging
by: Kong, Fanshuang, et al.
Published: (2024)