Results 111 to 120 of about 343,225 (391)

Detecting Blackholes and Volcanoes in Directed Networks [PDF]

, 2010
In this paper, we formulate a novel problem for finding blackhole and volcano patterns in a large directed graph. Specifically, a blackhole pattern is a group which is made of a set of nodes in a way such that there are only inlinks to this group from ...
Li, Zhongmou, Liu, Yanchi, Xiong, Hui
core  

Autonomous Self‐Evolving Research on Biomedical Data: The DREAM Paradigm

Advanced Science, EarlyView.
DREAM is a fully autonomous, self‐evolving biomedical research system capable of independently formulating scientific questions, performing analyses, and making new discoveries without human intervention. Validated in biomedical studies, DREAM significantly outperforms human scientists in research efficiency, accelerating scientific discovery and ...
Luojia Deng, Yijie Wu, Yongyong Ren, Hui Lu   +3 more
wiley   +1 more source

One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget [PDF]

arXiv, 2021
Introducing sparsity in a neural network has been an efficient way to reduce its complexity while keeping its performance almost intact. Most of the time, sparsity is introduced using a three-stage pipeline: 1) train the model to convergence, 2) prune the model according to some criterion, 3) fine-tune the pruned model to recover performance.
arxiv  

Generation of Neural Organoids and Their Application in Disease Modeling and Regenerative Medicine

Advanced Science, EarlyView.
Neural organoids provide a versatile platform for neurological research. Advances in organoid technology have partially achieved human neural tissue complexity in terms of tissue structure, cell diversity, and neural signaling, offering insights into neural disorders and regenerative strategies. Technology advances from biomaterials, bio‐manufacturing,
Ruiqi Huang, Feng Gao, Liqun Yu, Haokun Chen, Rongrong Zhu   +4 more
wiley   +1 more source

Potent Cross‐neutralizing Antibodies Reveal Vulnerabilities of Henipavirus Fusion Glycoprotein

Advanced Science, EarlyView.
Hendra and Nipah viruses (HNVs) pose significant threats to global health. This work reports potent cross‐neutralizing antibodies targeting the fusion glycoprotein (F) and reveals shared features of these antibodies and vulnerabilities of F, thereby guiding the rational design of countermeasures against HNVs and similar pathogens.
Yi Ren, Pengfei Fan, Xinghai Zhang, Ting Fang, Zhengshan Chen, Yanfeng Yao, Xiangyang Chi, Guanying Zhang, Xiaofan Zhao, Bingjie Sun, Fangxu Li, Zixuan Liu, Zhenwei Song, Baoyue Zhang, Cheng Peng, Entao Li, Yilong Yang, Jianmin Li, Sandra Chiu, Changming Yu   +19 more
wiley   +1 more source

Use of a hybrid intelligence decision tree to identify mature B‐cell neoplasms

Cytometry Part B: Clinical Cytometry, EarlyView., 2023
Abstract Background Mature B‐cell neoplasms are challenging to diagnose due to their heterogeneity and overlapping clinical and biological features. In this study, we present a new workflow strategy that leverages a large amount of flow cytometry data and an artificial intelligence approach to classify these neoplasms. Methods By combining mathematical
Inès Vergnolle, Theo Ceccomarini, Alban Canali, Jean‐Baptiste Rieu, François Vergez   +4 more
wiley   +1 more source

Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning

Advanced Science, EarlyView.
This work explores a machine learning (ML) model with electrochemical impedance spectroscopy (EIS) data to address two critical challenges in Lithium metal batteries (LMBs): capacity degradation trajectory and knee point (KP) estimation, for the first time.
Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama   +4 more
wiley   +1 more source

Distilled Gradual Pruning With Pruned Fine-Tuning

IEEE Transactions on Artificial Intelligence
Neural networks (NNs) have been driving machine learning progress in recent years, but their larger models present challenges in resource-limited environments. Weight pruning reduces the computational demand, often with performance degradation and long training procedures.
Federico Fontana, Romeo Lanzino, Marco Raoul Marini, Danilo Avola, Luigi Cinque, Francesco Scarcello, Gian Luca Foresti   +6 more
openaire   +3 more sources

Studies on Rejuvenation of Old, Unproductive 'Alphonso' Mango Trees in Orchards

Journal of Horticultural Sciences, 2011
A field trial on pruning was conducted from 2004 to 2009 to induce rejuvenation of twenty six year old, unproductive 'Alphonso' mango trees, at Indian Institute of Horticultural Research, Bangalore. In the study, three treatments imposed comprised of two
Y T N Reddy, Reju M Kurian
doaj   +1 more source

Towards Optimal Filter Pruning with Balanced Performance and Pruning Speed [PDF]

arXiv, 2020
Filter pruning has drawn more attention since resource constrained platform requires more compact model for deployment. However, current pruning methods suffer either from the inferior performance of one-shot methods, or the expensive time cost of iterative training methods.
arxiv