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Found 5 papers, 4 papers with code
Entropy-MCMC: Sampling from Flat Basins with Ease
Bayesian deep learning counts on the quality of posterior distribution estimation.
Long-tailed Classification from a Bayesian-decision-theory Perspective
Long-tailed classification poses a challenge due to its heavy imbalance in class probabilities and tail-sensitivity risks with asymmetric misprediction costs.
Trustworthy Long-Tailed Classification
To address these issues, we propose a Trustworthy Long-tailed Classification (TLC) method to jointly conduct classification and uncertainty estimation to identify hard samples in a multi-expert framework.
Ranked #19 on
Long-tail Learning
on CIFAR-10-LT (ρ=100)
Graph Communal Contrastive Learning
We argue that the community information should be considered to identify node pairs in the same communities, where the nodes insides are semantically similar.
Identifying Incorrect Classifications with Balanced Uncertainty
Uncertainty estimation is critical for cost-sensitive deep-learning applications (i. e. disease diagnosis).
