| 1 |
Meta-learning 개관 |
Meta-Learning in Neural Networks: A Survey |
Hospedales et al., 2020 |
메타러닝 전반 서베이, taxonomy·응용 정리 |
| 2 |
Meta-learning (gradient) |
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks (MAML) |
Finn et al., 2017 |
대표 gradient-based meta-learning |
| 3 |
Meta-learning (metric) |
Matching Networks for One Shot Learning |
Vinyals et al., 2016 |
초기 few-shot metric 기반 모델 |
| 4 |
Meta-learning (metric) |
Prototypical Networks for Few-shot Learning |
Snell et al., 2017 |
간단·강력한 metric-based baseline |
| 5 |
Meta-learning (model-based) |
Neural Processes |
Garnelo et al., 2018 |
함수 분포 기반, GP+NN 아이디어 |
| 6 |
Meta-learning (model-based) |
Attentive Neural Processes |
Kim et al., 2019 |
NP에 attention 도입, 성능·안정성 개선 |
| 7 |
Gradient↔︎Bayes 연결 |
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes |
Grant et al., 2018 |
MAML을 계층 베이지안으로 재해석 |
| 8 |
Bayesian meta-learning |
Gradient-EM Bayesian Meta-Learning |
Zou & Lu, 2020 |
gradient-EM 기반 베이지안 메타러닝 |
| 9 |
Bayesian meta-learning |
A Hierarchical Bayesian Model for Few-Shot Meta Learning |
Kim & Hospedales, ICLR 2024 |
계층 베이지안 few-shot 모형 제안 |
| 10 |
Bayesian meta-learning |
Bayesian Meta-Learning Through Variational Gaussian Processes (VMGP) |
Fortuin et al., 2021 |
변분 GP 기반 베이지안 메타러닝 |
| 11 |
Bayesian meta-learning (응용) |
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks |
(AITRICS), 약 2021–2022 |
불균형·OOD task에서 pooling 비율 조절 |
| 12 |
Multi-task GP 토대 |
Learning Gaussian Processes from Multiple Tasks |
Bonilla et al., ICML 2005 |
multi-task GP의 초기 계층 Bayes 정식화 |
| 13 |
Multi-task GP 토대 |
Multi-task Gaussian Process Prediction |
Bonilla et al., NIPS 2007 |
ICM/코리저널라이제이션 구조 대표 논문 |
| 14 |
Multi-task GP 토대 |
Multi-task Learning with Gaussian Processes |
K. M. A. Chai, 2010 |
multi-task GP 전반 비교·분석 |
| 15 |
Multi-task GP (딥 커널) |
Multitask Gaussian Processes (deep BNN kernels) |
(여러 저자), 2019 |
deep BNN에서 유도된 multitask GP 커널 |
| 16 |
Multi-task GP 이론 |
Learning Curves for Multi-task Gaussian Process Regression |
Ashton & Sollich, NIPS 2012 |
multi-task GP 학습 곡선(Bayes error) 분석 |
| 17 |
Multi-task GP 이론 |
Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes |
(Ashton 등), 2008 |
task 상관구조 vs 일반화오차 |
| 18 |
Multi-task GP 구조 |
Multi-output Gaussian Processes: Coregionalization Models Using Hadamard Product (ICM/LCM) |
Bonilla 계열 / 관련 저자 |
코리저널라이제이션 구조 기술 |
| 19 |
Multi-task GP (scalable) |
Scalable Multi-task Gaussian Processes with Neural Embedding of Coregionalization |
(예: Nguyen 등), 2022 |
신경 임베딩으로 풍부한 task 공분산 학습 |
| 20 |
GP 기반 meta-learning |
Learning to Learn with Gaussian Processes (GPML) |
Nguyen, Low, Jaillet, UAI 2021 |
대표 GP 기반 meta-learning, task kernel |
| 21 |
GP 기반 meta-learning |
Learning to Learn Dense Gaussian Processes for Few-Shot Learning |
(NeurIPS), 2021 |
dense inducing points 활용 GP meta-learning |
| 22 |
GP + uncertainty calibration |
Meta-learning to Calibrate Gaussian Processes with Deep Kernels for Regression Uncertainty Estimation |
(2024) |
deep kernel GP 불확실성 calibration |
| 23 |
GP + meta-learning (응용) |
Meta-learning Adaptive Deep Kernel Gaussian Processes for Molecular Property Prediction (ADKF-IFT) |
Chen et al., ICLR 2023 |
분자 property 예측용 deep kernel GP meta |
| 24 |
PAC-Bayes meta-learning 이론 |
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior |
Rothfuss et al., JMLR 2023 |
PACOH, PAC-Bayes 기반 meta-generalization |
| 25 |
PAC-Bayes meta-learning 이론 |
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees |
Rothfuss et al., 2021 |
PACOH 초기 버전, GP base learner |
| 26 |
PAC-Bayes + BNN prior |
Meta-Learning Bayesian Neural Network Priors Based on PAC-Bayesian Theory |
(예: Rothfuss/관련 저자), 2020 |
PAC-Bayes bound로 BNN prior meta-learning |
| 27 |
PAC-Bayes + 함수공간 prior |
Meta-Learning Reliable Priors in the Function Space (F-PACOH) |
Fortuin et al., NeurIPS 2021 |
함수공간 stochastic process prior 학습 |
| 28 |
Task similarity + meta-learning |
Task-Similarity Aware Meta-learning through Nonparametric Kernel Regression |
Venkitaraman, Hansson, Wahlberg, 2020 |
task를 RKHS에 두고 커널로 similarity 모델 |
| 29 |
Task similarity + Bayesian meta |
Bayesian Meta-Learning for Task Adaptation Using Expert-Inferred Task Similarities |
Aalto Univ. MSc Thesis, 2024 |
전문가가 준 similarity를 prior에 반영 |
| 30 |
Task similarity + 계층 Bayes |
Causal Similarity-Based Hierarchical Bayesian Models (Meta-Learning with Similarity of Causal Mechanisms) |
Wharrie & Kaski, 2023 |
인과 메커니즘 유사도로 pooling 결정 |