domain generalization
The ability of a model to perform well on unseen domains or datasets different from the training set. It aims to improve the generalization capabilities of algorithms by learning invariant features across varied conditions.
- An Effective Levelling Paradigm for Unlabeled Scenarios
- Approximate Domain Unlearning for Vision-Language Models
- Automatic Visual Instrumental Variable Learning for Confounding-Resistant Domain Generalization
- Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems
- EddyFormer: Accelerated Neural Simulations of Three-Dimensional Turbulence at Scale
- FedMGP: Personalized Federated Learning with Multi-Group Text-Visual Prompts
- Geometry-Aware Collaborative Multi-Solutions Optimizer for Model Fine-Tuning with Parameter Efficiency
- HIDISC: A Hyperbolic Framework for Domain Generalization with Generalized Category Discovery
- How Many Domains Suffice for Domain Generalization? A Tight Characterization via the Domain Shattering Dimension
- Learning a Cross-Modal Schrödinger Bridge for Visual Domain Generalization
- Leveraging Depth and Language for Open-Vocabulary Domain-Generalized Semantic Segmentation
- Memory-Integrated Reconfigurable Adapters: A Unified Framework for Settings with Multiple Tasks
- Timely Clinical Diagnosis through Active Test Selection
- Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement
- Vicinity-Guided Discriminative Latent Diffusion for Privacy-Preserving Domain Adaptation