- Network properties determine neural network performance🔍
- Network Properties Determine Neural Network Performance🔍
- Jianxi Gao on LinkedIn🔍
- Measuring Neural Network Performance🔍
- Neural Network Object Properties🔍
- Investigating the properties of neural network representations in ...🔍
- Enhancing deep neural network training efficiency and performance ...🔍
- Advancing Neural Network Performance through Emergence ...🔍
Network properties determine neural network performance
Network properties determine neural network performance - Nature
A mathematical framework that maps the neural network's performance to the network characters of the line graph governed by the edge dynamics of stochastic ...
Network properties determine neural network performance - PubMed
A mathematical framework that maps the neural network's performance to the network characters of the line graph governed by the edge dynamics of stochastic ...
Network properties determine neural network performance - NSF PAR
This paper explores three different model components to improve predictive performance over the ViEWS benchmark: a class of neural networks that ...
(PDF) Network properties determine neural network performance
The difficulty is rooted in many possible model configurations, each with different hyper-parameters and weighted architectures determined by noisy data. We ...
Network Properties Determine Neural Network Performance
We propose a method to predict the performance of neural network by computing the graph property of the corresponding graph.
Network properties determine neural network performance
The numerical results on 17 pre-trained ImageNet models across five benchmark datasets and one NAS benchmark indicate that our neural capacitance metric is a ...
Jianxi Gao on LinkedIn: I am excited to share that our latest work ...
... Network properties determine neural network performance" is out in Nature Communications! It was from the collaboration with Chunheng Jiang ...
Measuring Neural Network Performance: Latency and Throughput ...
When deploying a neural network in a real-world application, it is important to understand its performance characteristics, such as latency and ...
Neural Network Object Properties - MATLAB & Simulink - MathWorks
These properties determine the number of network subobjects (which include inputs, layers, outputs, targets, biases, and weights), and how they are connected.
Investigating the properties of neural network representations in ...
In this paper, we attempt to systematically measure representation properties and relationships to transfer performance (future learning), to gain more insight ...
Enhancing deep neural network training efficiency and performance ...
Firstly, based on the observation that parameters (weights and bias) of deep neural network change in certain rules during training process, the ...
Advancing Neural Network Performance through Emergence ... - arXiv
Our initialization scheme is grounded in the idea that by enhancing the emergent properties of neural networks from the beginning, we can ...
Neural network (machine learning) - Wikipedia
A network is typically called a deep neural network if it has at least two hidden layers. Artificial neural networks are used for various tasks, including ...
Neural Network Construction & Properties
Neural networks can be constructed to tackle specific tasks, but this requires flexibility and the possibility to experiment with different architectures ...
(PDF) Structure and Performance of Fully Connected Neural Networks
Each neural network is approached as a weighted and undirected graph of neurons and synapses, and centrality measures are computed after training. Results show ...
Neural Network - an overview | ScienceDirect Topics
The neural network has developed into a theoretical system with multiple network models. Use the neural network to construct the learning unit, and determine ...
How to measure the learning performance of neural network?
I assume you talk about a neural network for classification. Divide your training set in a real training set and a validation set using one ...
Designing an optimal neural network architecture - Emerald Insight
The performance of neural networks is determined by different factors, one of which is the neural network architecture. The success of a neural ...
Towards Understanding the Link Between Modularity and ... - arXiv
... performance, modularity, and many other network properties that were tested. We evolved a MAP-Elites grid of neural network solutions which ...
Performance comparison of neural network training algorithms in the ...
In determining the properties fiber reinforced concrete according to GA–ANN implementation, the water/cement ratio played slightly more ...