Nonlinear independent component analysis for principled disentanglement in unsupervised deep learning [0.03%]
无监督深度学习中用于原理分离的非线性独立成分分析
Aapo Hyvärinen,Ilyes Khemakhem,Hiroshi Morioka
Aapo Hyvärinen
A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called "disentanglement." Most approaches are heuristic and lack a proper theoretical foundation. In linear representa...
Exploiting noise as a resource for computation and learning in spiking neural networks [0.03%]
利用噪声作为脉冲神经网络计算和学习的资源
Gehua Ma,Rui Yan,Huajin Tang
Gehua Ma
Networks of spiking neurons underpin the extraordinary information-processing capabilities of the brain and have become pillar models in neuromorphic artificial intelligence. Despite extensive research on spiking neural networks (SNNs), mos...
Worldwide AI ethics: A review of 200 guidelines and recommendations for AI governance [0.03%]
全球人工智能伦理：对200项人工智能治理准则和建议的回顾
Nicholas Kluge Corrêa,Camila Galvão,James William Santos et al.
Nicholas Kluge Corrêa et al.
The utilization of artificial intelligence (AI) applications has experienced tremendous growth in recent years, bringing forth numerous benefits and conveniences. However, this expansion has also provoked ethical concerns, such as privacy b...
Building less-flawed metrics: Understanding and creating better measurement and incentive systems [0.03%]
构建更完善的指标：理解和创建更好的测量和激励体系
David Manheim
David Manheim
Metrics are useful for measuring systems and motivating behaviors in academia as well as in public policy, medicine, business, and other systems. Unfortunately, naive application of metrics to a system can distort the system and even underm...
Leveraging cell-cell similarity for high-performance spatial and temporal cellular mappings from gene expression data [0.03%]
利用细胞相似性进行高性能时空细胞映射以提高基因表达数据的质量
Md Tauhidul Islam,Lei Xing
Md Tauhidul Islam
Single-cell trajectory mapping and spatial reconstruction are two important developments in life science and provide a unique means to decode heterogeneous tissue formation, cellular dynamics, and tissue developmental processes. The success...
Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles [0.03%]
基于小神经元簇光遗传学刺激的功能连接图压缩感知技术
Phillip Navarro,Karim Oweiss
Phillip Navarro
Mapping functional connectivity between neurons is an essential step toward probing the neural computations mediating behavior. Accurately determining synaptic connectivity maps in populations of neurons is challenging in terms of yield, ac...
AIDMAN: An AI-based object detection system for malaria diagnosis from smartphone thin-blood-smear images [0.03%]
基于人工智能的疟疾诊断系统AIDMAN用于智能手机薄血涂片图像中的目标检测
Ruicun Liu,Tuoyu Liu,Tingting Dan et al.
Ruicun Liu et al.
Malaria is a significant public health concern, with ∼95% of cases occurring in Africa, but accurate and timely diagnosis is problematic in remote and low-income areas. Here, we developed an artificial intelligence-based object detection s...
Feiyang Yu,Mark Endo,Rayan Krishnan et al.
Feiyang Yu et al.
Artificial intelligence (AI) models for automatic generation of narrative radiology reports from images have the potential to enhance efficiency and reduce the workload of radiologists. However, evaluating the correctness of these reports r...
S3-CIMA: Supervised spatial single-cell image analysis for identifying disease-associated cell-type compositions in tissue [0.03%]
S3-CIMA：监督的 spatial single-cell 图像分析方法，用于识别组织中的疾病相关细胞类型组成
Sepideh Babaei,Jonathan Christ,Vivek Sehra et al.
Sepideh Babaei et al.
The spatial organization of various cell types within the tissue microenvironment is a key element for the formation of physiological and pathological processes, including cancer and autoimmune diseases. Here, we present S3-CIMA, a weakly s...
Stable clinical risk prediction against distribution shift in electronic health records [0.03%]
电子健康记录中的临床风险预测对抗分布变化的稳定性
Seungyeon Lee,Changchang Yin,Ping Zhang
Seungyeon Lee
The availability of large-scale electronic health record datasets has led to the development of artificial intelligence (AI) methods for clinical risk prediction that help improve patient care. However, existing studies have shown that AI m...