:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhu, Yihan, Liu, Gang, Inae, Eric, Luo, Tengfei, Jiang, Meng
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2505.10726
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

MolTextNet: A Two-Million Molecule-Text Dataset for Multimodal Molecular Learning
by: Zhu, Yihan, et al.
Published: (2025)

POINT$^{2}$: A Polymer Informatics Training and Testing Database
by: Xu, Jiaxin, et al.
Published: (2025)

Graph Diffusion Transformers are In-Context Molecular Designers
by: Liu, Gang, et al.
Published: (2025)

Open Polymer Challenge: Post-Competition Report
by: Liu, Gang, et al.
Published: (2025)

Motif-aware Attribute Masking for Molecular Graph Pre-training
by: Inae, Eric, et al.
Published: (2023)

Continual Learning in the Presence of Repetition
by: Hemati, Hamed, et al.
Published: (2024)

Learning Invariant Graph Representations Through Redundant Information
by: Halder, Barproda, et al.
Published: (2025)

Causal Neighbourhood Learning for Invariant Graph Representations
by: Job, Simi, et al.
Published: (2026)

Permutation-Invariant Representation Learning for Robust and Privacy-Preserving Feature Selection
by: Liu, Rui, et al.
Published: (2025)

Unsupervised Representation Learning - an Invariant Risk Minimization Perspective
by: Norman, Yotam, et al.
Published: (2025)

TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series
by: Piao, Xihao, et al.
Published: (2026)

Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
by: Qian, Fuyuan, et al.
Published: (2026)

EEGDM: Learning EEG Representation with Latent Diffusion Model
by: Wang, Shaocong, et al.
Published: (2025)

Domain Generalization In Robust Invariant Representation
by: Gupta, Gauri, et al.
Published: (2023)

Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization
by: Mao, Wenyu, et al.
Published: (2024)

Repetitive Contrastive Learning Enhances Mamba's Selectivity in Time Series Prediction
by: Yan, Wenbo, et al.
Published: (2025)

Rethinking Repetition Problems of LLMs in Code Generation
by: Dong, Yihong, et al.
Published: (2025)

MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features
by: Li, Huayu, et al.
Published: (2023)

Reinforcement Learning for Graph Coloring: Understanding the Power and Limits of Non-Label Invariant Representations
by: Cummins, Chase, et al.
Published: (2024)

DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling
by: Akhare, Deepak, et al.
Published: (2023)

Chemistry Integrated Language Model using Hierarchical Molecular Representation for Polymer Informatics
by: Ahn, Jihun, et al.
Published: (2025)

Causal Debiasing Medical Multimodal Representation Learning with Missing Modalities
by: Zhu, Xiaoguang, et al.
Published: (2025)

Robust Multimodal Representation Learning in Healthcare
by: Zhu, Xiaoguang, et al.
Published: (2026)

Learning Fair Invariant Representations under Covariate and Correlation Shifts Simultaneously
by: Li, Dong, et al.
Published: (2024)

Learning Fair Graph Representations with Multi-view Information Bottleneck
by: Liu, Chuxun, et al.
Published: (2025)

Modality as Heterogeneity: Node Splitting and Graph Rewiring for Multimodal Graph Learning
by: Zhang, Yihan, et al.
Published: (2026)

GraphPL: Leveraging GNN for Efficient and Robust Modalities Imputation in Patchwork Learning
by: Hu, Xingjian, et al.
Published: (2026)

Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments
by: Jin, Gaojie, et al.
Published: (2024)

Physics-Informed Teleconnection-Aware Transformer for Global Subseasonal-to-Seasonal Forecasting
by: Lyu, Tengfei, et al.
Published: (2025)

Implicit Neural Differential Model for Spatiotemporal Dynamics
by: Akhare, Deepak, et al.
Published: (2025)

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
by: Zhang, Zeyang, et al.
Published: (2024)

Controllable Molecular Generative Foundation Models
by: Zhu, Yihan, et al.
Published: (2026)

SC-GIR: Goal-oriented Semantic Communication via Invariant Representation Learning
by: Wanasekara, Senura Hansaja, et al.
Published: (2025)

Adaptive Repetition for Mitigating Position Bias in LLM-Based Ranking
by: Vardasbi, Ali, et al.
Published: (2025)

A Unified Invariant Learning Framework for Graph Classification
by: Sui, Yongduo, et al.
Published: (2025)

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
by: Luo, Kang, et al.
Published: (2024)

Seeking the Sufficiency and Necessity Causal Features in Multimodal Representation Learning
by: Chen, Boyu, et al.
Published: (2024)

Disentangled Representation Learning
by: Wang, Xin, et al.
Published: (2022)

Sufficient Invariant Learning for Distribution Shift
by: Kim, Taero, et al.
Published: (2022)

Dissecting the Failure of Invariant Learning on Graphs
by: Wang, Qixun, et al.
Published: (2024)