Imagen de Portada

Learning Repetition-Invariant Representations for Polymer Informatics

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhu, Yihan, Liu, Gang, Inae, Eric, Luo, Tengfei, Jiang, Meng
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Disentangled Representation Learning
por: Wang, Xin, et al.
Publicado: (2022)

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

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

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

Leveraging Superfluous Information in Contrastive Representation Learning
por: Yu, Xuechu
Publicado: (2024)

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

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

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

Representation Finetuning for Continual Learning
por: Luo, Haihua, et al.
Publicado: (2026)