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ArnetMiner: extraction and mining of academic social networks
The architecture and main features of the ArnetMiner system, which aims at extracting and mining academic social networks, are described and a unified modeling approach to simultaneously model topical aspects of papers, authors, and publication venues is proposed.
Expanded encyclopaedias of DNA elements in the human and mouse genomes
The authors summarize the data produced by phase III of the Encyclopedia of DNA Elements (ENCODE) project, a resource for better understanding of the human and mouse genomes, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development.
Self-supervised Learning: Generative or Contrastive
This survey takes a look into new self-supervised learning methods for representation in computer vision, natural language processing, and graph learning, and comprehensively review the existing empirical methods into three main categories according to their objectives.
Nighttime Dehazing with a Synthetic Benchmark
A novel synthetic method to simulate nighttime hazy images from daytime clear images, which first reconstructs the scene geometry, then simulates the light rays and object reflectance, and finally renders the haze effects, which demonstrates their superiority over state-of-the-art methods in terms of both image quality and runtime.
Consensus algorithms for biased labeling in crowdsourcing
Empowering Things With Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
It is shown how AI can empower the IoT to make it faster, smarter, greener, and safer, and some promising applications of AIoT that are likely to profoundly reshape the authors' world are summarized.
TopicNet: a framework for measuring transcriptional regulatory network change
This work proposes a method called TopicNet that applies latent Dirichlet allocation (LDA) to extract meaningful functional topics for a collection of genes regulated by a TF and defines a rewiring score to quantify the large-scale changes in the regulatory network in terms of topic change for a TF.
Machine Learning in Additive Manufacturing: A Review
The latest applications of machine learning (ML) in the additive manufacturing (AM) field are reviewed and different types of ML tasks, including regression, classification, and clustering are classified.
Knowledge modeling via contextualized representations for LSTM-based personalized exercise recommendation