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Meta-Learning

1524 directly classified papers

Papers per year

Papers

Mixed-Effect Thompson Sampling AISTATS 2023
Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approach NIPS 2023
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning NIPS 2023
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework AISTATS 2023
MORGAN: Meta-Learning-Based Few-Shot Open-Set Recognition via Generative Adversarial Network WACV 2023
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability AAAI 2023
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks NIPS 2023
Meta-AdaM: An Meta-Learned Adaptive Optimizer with Momentum for Few-Shot Learning NIPS 2023
Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator AAAI 2023
An Erudite Fine-Grained Visual Classification Model CVPR 2023
Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification WACV 2023
Episodic Multi-Task Learning with Heterogeneous Neural Processes NIPS 2023
Contextual Stochastic Bilevel Optimization NIPS 2023
Learning Functional Transduction NIPS 2023
Sample-efficient Multi-objective Molecular Optimization with GFlowNets NIPS 2023
Recasting Continual Learning as Sequence Modeling NIPS 2023
Meta Learning in Decentralized Neural Networks: Towards More General AI AAAI 2023
Learning Large-scale Neural Fields via Context Pruned Meta-Learning NIPS 2023
Multiple Thinking Achieving Meta-Ability Decoupling for Object Navigation ICML 2023
Equilibrium Point Learning ACML 2023
Hypernetworks for Zero-Shot Transfer in Reinforcement Learning AAAI 2023
Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning AAAI 2023
Quantum Multi-Agent Meta Reinforcement Learning AAAI 2023
Multi-Agent Meta-Reinforcement Learning: Sharper Convergence Rates with Task Similarity NIPS 2023
Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning EACL 2023