Personalized Treatment Outcome Prediction from Scarce Data via Dual-Channel Knowledge Distillation and Adaptive Fusion

arXiv:2510.26444 · cs.LG, cs.AI · Submitted 2025-10-30 · Read on arXiv

cs.LG, cs.AI

Submitted: 2025-10-30

Updated: 2026-08-29

Comments: Accepted to IEEE TETCI

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Fidelity — 176× in this paper · explained in 2 episodes
• Accuracy — 23× in this paper · explained in 1 episode
• Transfer Learning — 23× in this paper · explained in 10 episodes
• Distillation — 20× in this paper · explained in 2 episodes
• Knowledge Distillation — 15× in this paper · explained in 11 episodes
• Data Fusion — 13× in this paper · explained in 3 episodes
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Interpretability — 7× in this paper · explained in 15 episodes
• Loss Function — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Activation Function — 4× in this paper · explained in 1 episode
• Attention Mechanism — 4× in this paper · explained in 2 episodes
• Core — 4× in this paper · explained in 2 episodes
• Decoupling — 3× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Active Learning — 2× in this paper · explained in 6 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Explainability — 1× in this paper · explained in 3 episodes
• Federated Learning — 1× in this paper · explained in 14 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

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