AIMC Topic: Neural Networks, Computer

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Time series (re)sampling using Generative Adversarial Networks.

Neural networks : the official journal of the International Neural Network Society
We propose a novel bootstrap procedure for time series data based on Generative Adversarial networks (GANs). We show that the dynamics of common stationary time series processes can be learned by GANs and demonstrate that GANs trained on a single sam...

Not all edges are peers: Accurate structure-aware graph pooling networks.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in graph-related tasks. For graph classification task, an elaborated pooling operator is vital for learning graph-level representations. Most pooling operators derived from exist...

MG-CNN: A deep CNN to predict saddle points of matrix games.

Neural networks : the official journal of the International Neural Network Society
Finding the saddle point of a matrix game is a classical problem that arises in various fields, e.g., economics, computer science, and engineering. The standard problem-solving methods consist of formulating the problem as a linear program (LP). Howe...

MultiscaleDTA: A multiscale-based method with a self-attention mechanism for drug-target binding affinity prediction.

Methods (San Diego, Calif.)
The task of predicting drug-target affinity (DTA) plays an increasingly important role in the early stage of in silico drug discovery and development. Currently, a variety of machine learning-based methods have been presented for DTA prediction and a...

Identity and Gender Recognition Using a Capacitive Sensing Floor and Neural Networks.

Sensors (Basel, Switzerland)
In recent publications, capacitive sensing floors have been shown to be able to localize individuals in an unobtrusive manner. This paper demonstrates that it might be possible to utilize the walking characteristics extracted from a capacitive floor ...

Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks.

Molecules (Basel, Switzerland)
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morpholog...

Self-supervised graph neural network with pre-training generative learning for recommendation systems.

Scientific reports
The case assignment system is an essential system of case management and assignment within the procuratorate and is an important aspect of judicial fairness and efficiency. However, existing methods mostly use manual or random case assignment, which ...

Deep learning for neural decoding in motor cortex.

Journal of neural engineering
. Neural decoding is an important tool in neural engineering and neural data analysis. Of various machine learning algorithms adopted for neural decoding, the recently introduced deep learning is promising to excel. Therefore, we sought to apply deep...

Teaching Quality Evaluation of Animal Science Specialty Based on IPSO-BP Neural Network Model.

Computational intelligence and neuroscience
Teaching quality evaluation is one of the most commonly used educational evaluation methods, which is used to evaluate teachers' teaching ability and teaching effect. In order to improve the effectiveness and accuracy of teaching quality evaluation, ...

Security Analysis of Social Network Topic Mining Using Big Data and Optimized Deep Convolutional Neural Network.

Computational intelligence and neuroscience
This research aims to conduct topic mining and data analysis of social network security using social network big data. At present, the main problem is that users' behavior on social networks may reveal their private data. The main contribution lies i...