Abstract: The interconnection of smart medical devices is becoming an important trend in healthcare. Due to the differences in task requirements and power reserves of smart medical device clusters, if ...

Department of Materials Science and Engineering, Indian Institute of Technology, Delhi-110016, India Department of Chemistry, Indian Institute of Technology, Delhi-110016, India ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...

Department of Chemistry and Chemical Engineering, Education and Research Center for Smart Energy and Materials, Inha University, Incheon 22212, Republic of Korea ...

With the recent popularity of neural networks comes the need for efficient serving of inference workloads. A neural network inference workload can be represented as a computational graph with nodes as ...

Abstract: In this paper, we design Graph Neural Networks (GNNs) with attention mechanisms to tackle an important yet challenging nonlinear regression problem: massive network localization. We first ...

Medical imaging can be used to diagnose diseases, monitor their progression, and evaluate their treatment, often providing immediate and accurate feedback that can lead to faster responses and better ...

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...