Explore the latest peer-reviewed research with AI-generated summaries, key findings, and insights for easy understanding. All content is legally sourced from academic metadata with links to original papers.
Kickstart your research with this practical, bestselling guide to doing social network analysis. Get to grips with the mathematical foundations and learn how to use software tools such as NeTDraw and...
This five-day workshop, led by Donald Green from Columbia University, provides a comprehensive guide to designing, executing, and interpreting field experiments across various social science fields.
This paper presents SimCLR: a simple framework for contrastive learning of visual representations. A linear classifier trained on self-supervised representations learned by SimCLR achieves 76.5% top-1...
This research explores Introduction to Non-linear Mechanics, contributing new insights to the field of Physics & Space Science.
This research explores Phase Transitions and Critical Phenomena, contributing new insights to the field of Physics & Space Science.
Large deep neural networks are powerful, but exhibit undesirable behaviors such as memorization and sensitivity to adversarial examples. Our experiments on the ImageNet-2012, CIFAR-10, CIFAR-100, Goog...
Abstract While recent language models have the ability to take long contexts as input, relatively little is known about how well they use longer context. In particular, we observe that performance is...
Bayesian parameter estimation is fast becoming the language of gravitational-wave astronomy. BILBY has additional functionality to do population studies using hierarchical Bayesian modeling.
This research explores Knowledge Representation and Reasoning, contributing new insights to the field of Artificial Intelligence.
This research explores epidemiology of Parkinson's disease, contributing new insights to the field of Physics & Space Science.
A large range of sophisticated brain image analysis tools have been developed by the neuroscience community, greatly advancing the field of human brain mapping. Notably, CAT incorporates multiple qual...
«Биомедицинская информатика. Сегодня на русскоязычном рынке литературы это единственное подобное издание по полноте, новизне и практикоориентированности.
Deep Neural Networks (DNNs) are becoming common in "learning-enabled" time-critical applications such as autonomous driving and robotics. Compared to the layer-wise partitioning approach (DeepTrust^RT...
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. Extensive experimental results demonstrate the effectiveness of our DEA-Net,...
This research explores Review on YOLOv8 and Its Advancements, contributing new insights to the field of Artificial Intelligence.
When a person is diagnosed with cancer, difficult decisions about treatments need to be made. In a next step we provided personalized context to these numbers, both in verbal statements and in narrati...
Disambiguating concepts and entities in a context sensitive way is a fundamental problem in natural language processing. In this work we analyze approaches that utilize this information to arrive at c...
The emergence of vaccinomics and system vaccinology represents a transformative shift in immunization strategies, advocating for personalized vaccines tailored to individual genetic and immunological...
Rapid advancements in the field of artificial intelligence (AI) have opened up unprecedented opportunities to revolutionize various scientific domains, including immunology and genetics. Therefore, it...
Systems neuroscience explores the intricate organization and dynamic function of neural circuits and networks within the brain. These include brain-machine interfaces (BMIs) for neural prosthetics, co...