6 papers · 1 filter
Preliminary Insights in Chronos Frequency Data Understanding and Reconstruction
Alessandro Pagani, Marco Cominelli, Liying Han +11
This paper presents a preliminary analysis of the ability of Chronos foundation model to process and internally represent frequency domain information. Foundation models that proce…
SWAN: World-Aware Adaptive Multimodal Networks for Runtime Variations
Jason Wu, Shir-Kang Scott Jin, Yuyang Yuan +4
Multimodal deep neural networks deployed in realistic environments must contend with runtime variations: changes in modality quality, overall input complexity, and available platfo…
ADMN: A Layer-Wise Adaptive Multimodal Network for Dynamic Input Noise and Compute Resources
Jason Wu, Yuyang Yuan, Kang Yang +2
Multimodal deep learning systems are deployed in dynamic scenarios due to the robustness afforded by multiple sensing modalities. Nevertheless, they struggle with varying compute r…
NAROCE: A Neural Algorithmic Reasoner Framework for Online Complex Event Detection
Liying Han, Gaofeng Dong, Xiaomin Ouyang +3
Modern machine learning models excel at detecting individual actions, objects, or scene attributes from short, local observations. However, many real-world tasks, such as in smart…
Toward Foundation Models for Online Complex Event Detection in CPS-IoT: A Case Study
Liying Han, Gaofeng Dong, Xiaomin Ouyang +3
Complex events (CEs) play a crucial role in CPS-IoT applications, enabling high-level decision-making in domains such as smart monitoring and autonomous systems. However, most exis…
Risk-aware Classification via Uncertainty Quantification
Murat Sensoy, Lance M. Kaplan, Simon Julier +2
Autonomous and semi-autonomous systems are using deep learning models to improve decision-making. However, deep classifiers can be overly confident in their incorrect predictions,…