4 citations · 4 across the 3 of their papers we have counts for
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cs.LG2024
Flatness Improves Backbone Generalisation in Few-shot Classification
Rui Li, Martin Trapp, Marcus Klasson +1
Deployment of deep neural networks in real-world settings typically requires adaptation to new tasks with few examples. Few-shot classification (FSC) provides a solution to this pr…
cs.LG2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
Rui Li, ST John, Arno Solin
Approximate inference in Gaussian process (GP) models with non-conjugate likelihoods gets entangled with the learning of the model hyperparameters. We improve hyperparameter learni…
cs.LG2022★ 4 cited
Test-Time Training for Graph Neural Networks
Yiqi Wang, Chaozhuo Li, Wei Jin +4
Graph Neural Networks (GNNs) have made tremendous progress in the graph classification task. However, a performance gap between the training set and the test set has often been not…