In this work, we propose an uncertainty-aware fusion scheme to effectively fuse inputs that might suffer from a range of known and unknown degradation. Specifically, we analyze a number of uncertainty measures, each of which captures a different aspect of uncertainty, and we propose a novel ...
[Daily多模态] MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model 好想换个名字 早 4 人赞同了该文章 在训练中加入高斯分布作为不确定性估计, CVPR 2023 accept。 Motivation 多模态语义理解通常必须处理不确定性,这意味着获得的消息往往指向多个目标。很少有人研究这种不确定性的建模,特别是在...
we propose a multimodal deep learning approach to detect hardware Trojans and evaluate the results from both early fusion and late fusion strategies. We also estimate the uncertainty quantification metrics of each prediction for risk-aware decision-making. The results not only validate the effectiveness...
The whole framework is trained end-to-end by minimizing a loss function quantifying the errors before and after the fusion of information from each modality. Our main contributions are, thus, the following: 1. We propose a new hybrid fusion architecture for multimodal medical images composed of ...
an uncertainty-aware graph deep learning method for outcome prediction following mechanical thrombectomy in acute ischemic stroke patients. This approach enhances the interpretability of deep learning models and incorporates several neuroimaging variables extracted from multimodal CT images, such as ASPECT score...
Uncertainty-aware flexibility modeling and aggregation with high accuracy. • Indicator to compute the risk of insufficient flexibility potentials. • Application of the developed methods to households and renewable energy communities. Abstract The increasing share of volatile renewables in power systems ...
To address these issues, we introduce the Spatiotemporal Zero-Inflated Tweedie Graph Neural Networks (STZITD-GNN), the first uncertainty-aware probabilistic graph deep learning model in road-level daily-basis traffic crash prediction for multi-steps. Our model combines the interpretability of the ...
Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge 18 Sep 2023 · Alex C. Stutts, Danilo Erricolo, Sathya Ravi, Theja Tulabandhula, Amit Ranjan Trivedi · Edit social preview In the expanding landscape of AI-enabled robotics, ...
Paper tables with annotated results for Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
II. MULTIMODAL FUSION BY UNCERTAINTY COMPENSATION For many applications one can get imp...A. Katsamanis, G. Papandreou, V. Pitsikalis, and P. Maragos, "Mul- timodal fusion by adaptive compensation for feature uncertainty with application to audiovisual speech recognition," in ...