Name
Abstract | ||
|---|---|---|
Abstract We compare the use of artiflcial neural networks and Gaussian processes for forecasting. We show that Ar- tiflcial Neural Networks have the advantage of being utilisable with greater volumes of data but Gaussian processes can more easily be utilised to deal with non- stationarity. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.2991/jcis.2006.7 | JCIS |
Keywords | Field | DocType |
neural network,gaussian processes,prediction,supervised learning,gaussian process,artificial neural network | Feedforward neural network,Rectifier (neural networks),Computer science,Stochastic neural network,Recurrent neural network,Time delay neural network,Types of artificial neural networks,Artificial intelligence,Deep learning,Artificial neural network,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Colin Fyfe | 1 | 508 | 55.62 |
| Tzai-der Wang | 2 | 119 | 15.65 |
| Shang-jen Chuang | 3 | 10 | 3.76 |