Search Results for author:
Found 3 papers, 1 papers with code
Posterior Re-calibration for Imbalanced Datasets
Neural Networks can perform poorly when the training label distribution is heavily imbalanced, as well as when the testing data differs from the training distribution.
Ranked #31 on
Long-tail Learning
on CIFAR-100-LT (ρ=10)
Who2com: Collaborative Perception via Learnable Handshake Communication
In this paper, we propose the problem of collaborative perception, where robots can combine their local observations with those of neighboring agents in a learnable way to improve accuracy on a perception task.
UNO: Uncertainty-aware Noisy-Or Multimodal Fusion for Unanticipated Input Degradation
Specifically, we analyze a number of uncertainty measures, each of which captures a different aspect of uncertainty, and we propose a novel way to fuse degraded inputs by scaling modality-specific output softmax probabilities.
