Generative Classifier for Domain Generalization

arXiv:2504.02272 · cs.CV · Submitted 2025-04-03 · Read on arXiv

cs.CV

Submitted: 2025-04-03

Updated: 2026-09-27

Code: https://github.com/longshaocong/GCDG

Terminology

Generalization — 120× in this paper · explained in 13 episodes
Generalizability — 15× in this paper · explained in 6 episodes
Adaptation — 11× in this paper · explained in 1 episode
Benchmark — 11× in this paper · explained in 2 episodes
Accuracy — 9× in this paper · explained in 1 episode
Heterogeneity Learning Classifier — 9× in this paper
Spurious Correlation Blocking — 9× in this paper
Diverse Component Balancing — 8× in this paper
AUC — 6× in this paper · explained in 2 episodes
Alignment — 6× in this paper · explained in 1 episode
Distribution Shift — 6× in this paper · explained in 6 episodes
Linear probe — 6× in this paper · explained in 2 episodes
Representation Learning — 5× in this paper · explained in 2 episodes
Domain Adaptation — 4× in this paper · explained in 5 episodes
Generative Modeling — 4× in this paper · explained in 3 episodes
Optimal Transport — 4× in this paper · explained in 5 episodes
Regularization — 4× in this paper · explained in 3 episodes
Transfer Learning — 4× in this paper · explained in 10 episodes
Ablation — 3× in this paper · explained in 1 episode
Ablation study — 3× in this paper · explained in 1 episode
Adam — 3× in this paper · explained in 2 episodes
Consistency — 3× in this paper · explained in 3 episodes
Contrastive Learning — 3× in this paper · explained in 5 episodes
Gaussian Mixture Models — 3× in this paper
Generative Classifier-driven Domain Generalization — 3× in this paper
Adversarial Attacks — 2× in this paper · explained in 1 episode
Adversarial Training — 2× in this paper · explained in 1 episode
Mixture of Experts — 2× in this paper · explained in 2 episodes
Transformer — 2× in this paper · explained in 2 episodes
Adaptivity — 1× in this paper · explained in 1 episode
Area Under Curve — 1× in this paper
Calibration — 1× in this paper · explained in 7 episodes
Clustering — 1× in this paper · explained in 2 episodes
Computational overhead — 1× in this paper · explained in 2 episodes
Distillation — 1× in this paper · explained in 2 episodes
Domain Shift — 1× in this paper · explained in 4 episodes
Ensemble Learning — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Gaussian Mixture Model (GMM) — 1× in this paper · explained in 2 episodes
Generative Model — 1× in this paper · explained in 2 episodes
Generative Models — 1× in this paper · explained in 2 episodes
Half Total Error Rate — 1× in this paper
Multi-Layer Perceptron — 1× in this paper
Robustness — 1× in this paper · explained in 5 episodes
Unified Framework — 1× in this paper · explained in 5 episodes
Verification — 1× in this paper · explained in 2 episodes

Sources

Towards Principled Disentanglement for Domain Generalization

Terminology

Sources

Related papers