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TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models
However, the reliability of these estimates has been overlooked, even though the quality of the evaluation hinges entirely on their accuracy.
4f00921114932db3f8662a41b44ee68f-Supplemental.pdf
However, it remains a challenge to extract reliable inference from complexdatasets with uncertainty quantification.
4f00921114932db3f8662a41b44ee68f-Paper.pdf
However, it remains a challenge to extract reliable inference from complexdatasets with uncertainty quantification.
Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery
However, the pretrained model may not provide an ideal optimization starting point for the test-time optimization.
SupplementaryMaterialof TowardsEnablingMeta-Learning fromTargetModels
In this experiment, we modify ProtoNet slightly to fit regression problem. In detail, we try to meta-learn an embedding functionφ: R R100, with assistance of which the similarity-based regressionmodelg(;{φ(xi)|(xi,yi) S})workswellacrossalltasks.
TowardsEnablingMeta-Learning fromTargetModels
It is often realized through optimizing a metamodel withtheevaluation lossoftask-specific solvers.