Deep physical informed neural networks for metamaterial design

Z Fang, J Zhan - Ieee Access, 2019 - ieeexplore.ieee.org
In this paper, we propose a physical informed neural network approach for designing the
electromagnetic metamaterial. The approach can be used to deal with various practical …

T-recsys: A novel music recommendation system using deep learning

F Fessahaye, L Perez, T Zhan, R Zhang… - 2019 IEEE …, 2019 - ieeexplore.ieee.org
A recommendation system is a program that utilizes techniques to suggest to a user items
that they would likely prefer. This paper focuses on an approach to improving music …

Hand gesture recognition with convolution neural networks

F Zhan - 2019 IEEE 20th international conference on …, 2019 - ieeexplore.ieee.org
Hand gestures are the most common forms of communication and have great importance in
our world. They can help in building safe and comfortable user interfaces for a multitude of …

Deep learning for link prediction in dynamic networks using weak estimators

C Chiu, J Zhan - IEEE Access, 2018 - ieeexplore.ieee.org
Link prediction is the task of evaluating the probability that an edge exists in a network, and it
has useful applications in many domains. Traditional approaches rely on measuring the …

Machine learning models for paraphrase identification and its applications on plagiarism detection

E Hunt, R Janamsetty, C Kinares, C Koh… - … Conference on Big …, 2019 - ieeexplore.ieee.org
Paraphrase Identification or Natural Language Sentence Matching (NLSM) is one of the
important and challenging tasks in Natural Language Processing where the task is to …

Modeling cell communication with time-dependent signaling hypergraphs

MR Schwob, J Zhan, A Dempsey - IEEE/ACM transactions on …, 2019 - ieeexplore.ieee.org
Signaling pathways describe a group of molecules in a cell that collaborate to control one or
more cell functions, such as cell division or cell death. The pathways communicate by …

Whole time series data streams clustering: dynamic profiling of the electricity consumption

K Gajowniczek, M Bator, T Ząbkowski - Entropy, 2020 - mdpi.com
Data from smart grids are challenging to analyze due to their very large size, high
dimensionality, skewness, sparsity, and number of seasonal fluctuations, including daily and …

A study of ensemble methods for cyber security

N Lower, F Zhan - 2020 10th Annual Computing and …, 2020 - ieeexplore.ieee.org
Ensemble methods for machine learning serve to increase the predictive power of
preexisting models by applying a meta-algorithm on top of the underlying workings of one or …

Deep learning based shopping assistant for the visually impaired

D Pintado, V Sanchez, E Adarve, M Mata… - 2019 IEEE …, 2019 - ieeexplore.ieee.org
Contemporary developments in computer vision and artificial intelligence show promise to
greatly improve the lives of those with disabilities. In this paper, we propose one such …

Spotting the stock and crypto markets' rings of fire: measuring change proximities among spillover dependencies within inter and intra-market asset classes

H Setiawan, M Bhaduri - Applied Network Science, 2023 - Springer
Crypto assets have lately become the chief interest of investors around the world. The
excitement around, along with the promise of the nascent technology led to enormous …