Results 71 to 80 of about 5,739,313 (302)

Information Transmission Strategies for Self‐Organized Robotic Aggregation

Advanced Robotics Research, EarlyView.
In this review, we discuss how information transmission influences the neighbor‐based self‐organized aggregation of swarm robots. We focus specifically on local interactions regarding information transfer and categorize previous studies based on the functions of the information exchanged.
Shu Leng, Zihan Li, Yifeng Shao, Jinhao Liu, Li Yu, Shuguang Li   +5 more
wiley   +1 more source

Adversarial Sample Detection in Computer Vision:A Survey [PDF]

Jisuanji kexue
With the increase in data volume and improvement in hardware performance,deep learning(DL) has made significant progress in the field of computer vision.However,deep learning models are vulnerable to adversarial samples,causing significant changes in the
ZHANG Xin, ZHANG Han, NIU Manyu, JI Lixia
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions

Advanced Science, EarlyView.
CellPolaris decodes how transcription factors guide cell fate by building gene regulatory networks from transcriptomic data using transfer learning. It generates tissue‐ and cell‐type‐specific networks, identifies master regulators in cell state transitions, and simulates TF perturbations in developmental processes.
Guihai Feng, Xin Qin, Jiahao Zhang, Wuliang Huang, Yiyang Zhang, Wentao Cui, Yao Chen, Shirui Li, Wenhao Liu, Yao Tian, Yana Liu, Jingxi Dong, Ping Xu, Zhenpeng Man, Guole Liu, Zhongming Liang, Xinlong Jiang, Xiaodong Yang, Pengfei Wang, Ge Yang, Hongmei Wang, Xuezhi Wang, Ming‐Han Tong, Yuanchun Zhou, Shihua Zhang, Yiqiang Chen, Yong Wang, Xin Li   +27 more
wiley   +1 more source

Adversarial learning for counterfactual fairness

Machine Learning, 2022
In recent years, fairness has become an important topic in the machine learning research community. In particular, counterfactual fairness aims at building prediction models which ensure fairness at the most individual level. Rather than globally considering equity over the entire population, the idea is to imagine what any individual would look like ...
Grari, Vincent, Lamprier, Sylvain, Detyniecki, Marcin   +2 more
openaire   +2 more sources

Unpaired Learning‐Enabled Nanotube Identification from AFM Images

Advanced Science, EarlyView.
Identifying nanotubes on rough substrates is notoriously challenging for conventional image analysis. This work presents an unpaired deep learning approach that automatically extracts nanotube networks from atomic force microscopy images, even on complex polymeric surfaces used in roll‐to‐roll printing.
Soyoung Na, Soobin Park, Younsu Jung, Jinhwa Park, Jimin Hong, Jihyun Lee, Albert Kim, Bongjun Kim, Gyoujin Cho, Eunju Cha, Seung Hyun Song   +10 more
wiley   +1 more source

Targeted Adversarial Learning Optimized Sampling [PDF]

The Journal of Physical Chemistry Letters, 2019
Abstract Boosting transitions of rare events is critical to modern-day simulations of complex dynamic systems. We present a novel approach to modify the potential energy surface in order to drive the system to a user-defined target distribution where the free energy barrier is lowered.
Jun Zhang, Yi Isaac Yang, Frank Noé
openaire   +2 more sources

Diffusion‐MRI‐Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains

Advanced Science, EarlyView.
We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu, Minhui Ouyang, Shufang Tan, Jianlin Guo, Ziqin Zhang, Xuan Liu, Risheng Liu, Hao Huang   +7 more
wiley   +1 more source

SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL

Tạp chí Khoa học Đại học Đà Lạt
Artificial intelligence (AI) has found applications across various sectors and industries, offering numerous advantages to human beings. One prominent area where AI has made significant contributions is in machine learning models.
Thanh Son Phan, Quang Hua Ta, Duy Trung Pham, Phi Ho Truong   +3 more
doaj   +1 more source

Adversarially Learned Inference

, 2016
We introduce the adversarially learned inference (ALI) model, which jointly learns a generation network and an inference network using an adversarial process. The generation network maps samples from stochastic latent variables to the data space while the inference network maps training examples in data space to the space of latent variables.
Dumoulin, Vincent, Belghazi, Ishmael, Poole, Ben, Mastropietro, Olivier, Lamb, Alex, Arjovsky, Martin, Courville, Aaron   +6 more
openaire   +2 more sources