The evolution of distributed systems for graph neural networks and their origin in graph processing and deep learning: A survey
Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …
neural network architecture is capable of processing graph structured data and bridges the …
Deep learning for time series forecasting: a survey
Time series forecasting has become a very intensive field of research, which is even
increasing in recent years. Deep neural networks have proved to be powerful and are …
increasing in recent years. Deep neural networks have proved to be powerful and are …
Pysyft: A library for easy federated learning
PySyft is an open-source multi-language library enabling secure and private machine
learning by wrapping and extending popular deep learning frameworks such as PyTorch in …
learning by wrapping and extending popular deep learning frameworks such as PyTorch in …
Communication-efficient edge AI: Algorithms and systems
Artificial intelligence (AI) has achieved remarkable breakthroughs in a wide range of fields,
ranging from speech processing, image classification to drug discovery. This is driven by the …
ranging from speech processing, image classification to drug discovery. This is driven by the …
Variability and reproducibility in deep learning for medical image segmentation
Medical image segmentation is an important tool for current clinical applications. It is the
backbone of numerous clinical diagnosis methods, oncological treatments and computer …
backbone of numerous clinical diagnosis methods, oncological treatments and computer …
Artificial intelligence governance for businesses
J Schneider, R Abraham, C Meske… - Information Systems …, 2023 - Taylor & Francis
While artificial intelligence (AI) governance is thoroughly discussed on a philosophical,
societal, and regulatory level, few works target companies. We address this gap by deriving …
societal, and regulatory level, few works target companies. We address this gap by deriving …
Deep learning in smart grid technology: A review of recent advancements and future prospects
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …
a promising landscape for high grid reliability and efficient energy management. This …
Towards efficient generative large language model serving: A survey from algorithms to systems
In the rapidly evolving landscape of artificial intelligence (AI), generative large language
models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However …
models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However …
Distributed artificial intelligence-as-a-service (DAIaaS) for smarter IoE and 6G environments
Artificial intelligence (AI) has taken us by storm, helping us to make decisions in everything
we do, even in finding our “true love” and the “significant other”. While 5G promises us high …
we do, even in finding our “true love” and the “significant other”. While 5G promises us high …
Personalized real-time federated learning for epileptic seizure detection
Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by
the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant …
the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant …