{"total":23,"rows":[{"id":"2110.14012","title":"Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification","created":"2021-10-26","cited_by_count":80,"area":null},{"id":"2409.04720","title":"A Comprehensive Survey on Evidential Deep Learning and Its Applications","created":"2024-09-07","cited_by_count":25,"area":null},{"id":"2203.11378","title":"HyperShot: Few-Shot Learning by Kernel HyperNetworks","created":"2022-03-21","cited_by_count":24,"area":null},{"id":"2209.00517","title":"The Neural Process Family: Survey, Applications and Perspectives","created":"2022-09-01","cited_by_count":23,"area":null},{"id":"2205.15745","title":"HyperMAML: Few-Shot Adaptation of Deep Models with Hypernetworks","created":"2022-05-31","cited_by_count":17,"area":null},{"id":"2210.03067","title":"Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction","created":"2022-10-06","cited_by_count":17,"area":null},{"id":"2203.03059","title":"Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?","created":"2022-03-06","cited_by_count":13,"area":null},{"id":"2106.00252","title":"Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning","created":"2021-06-01","cited_by_count":10,"area":null},{"id":"2203.12768","title":"Multidimensional Belief Quantification for Label-Efficient Meta-Learning","created":"2022-03-23","cited_by_count":9,"area":null},{"id":"2302.11709","title":"Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes","created":"2023-02-23","cited_by_count":8,"area":null},{"id":"2101.11201","title":"Similarity of Classification Tasks","created":"2021-01-27","cited_by_count":7,"area":null},{"id":"2208.10559","title":"Transductive Decoupled Variational Inference for Few-Shot Classification","created":"2022-08-22","cited_by_count":7,"area":null},{"id":"2106.04802","title":"Probabilistic task modelling for meta-learning","created":"2021-06-09","cited_by_count":4,"area":null},{"id":"2303.17768","title":"Scalable Bayesian Meta-Learning through Generalized Implicit Gradients","created":"2023-03-31","cited_by_count":4,"area":null},{"id":"2108.00785","title":"Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization","created":"2021-08-02","cited_by_count":2,"area":null},{"id":"2301.01400","title":"Task Weighting in Meta-learning with Trajectory Optimisation","created":"2023-01-04","cited_by_count":2,"area":null},{"id":"2510.19425","title":"Neural Variational Dropout Processes","created":"2025-10-22","cited_by_count":2,"area":null},{"id":"2110.11664","title":"GCCN: Global Context Convolutional Network","created":"2021-10-22","cited_by_count":1,"area":null},{"id":"2110.13188","title":"Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning","created":"2021-10-25","cited_by_count":1,"area":null},{"id":"2109.10824","title":"Learning by Examples Based on Multi-level Optimization","created":"2021-09-22","cited_by_count":0,"area":null},{"id":"2210.02796","title":"Hypernetwork approach to Bayesian MAML","created":"2022-10-06","cited_by_count":0,"area":null},{"id":"2306.09702","title":"A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning","created":"2023-06-16","cited_by_count":0,"area":null},{"id":"2410.01476","title":"Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks","created":"2024-10-02","cited_by_count":0,"area":null}],"next_cursor":null}