Discovering Hierarchy-Grounded Domains with Adaptive Granularity for Clinical Domain Generalization
cs.LG, cs.AI
Submitted: 2025-06-08
Updated: 2026-09-13
Comments: Accepted by CIKM 2026 (Oral)
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Bridging Stepwise Lab-Informed Pretraining and Knowledge-Guided Learning for Diagnostic Reasoning
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
- Renaissance of RNNs in Streaming Clinical Time Series: Compact Recurrence Remains Competitive with Transformers
- Does Bigger Mean Better? Comparitive Analysis of CNNs and Biomedical Vision Language Modles in Medical Diagnosis
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks