Name
Abstract | ||
|---|---|---|
•The first unified neural model of information fusion in perception is proposed.•A unified theoretical formalization of different perceptual tasks is present.•The reasonable neural circuit can calculate intractable posterior distribution.•The neural model performs Bayesian inference optimally is strictly proved.•Divisive normalization in cortex is linked to Bayesian posterior distribution. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.neucom.2019.05.067 | Neurocomputing |
Keywords | Field | DocType |
Multisensory integration,Causal inference,Unified neural circuit,Importance sampling,Probabilistic population codes | Causal inference,Importance sampling,Bayesian inference,Multisensory integration,Neural coding,Posterior probability,Artificial intelligence,Probabilistic logic,Artificial neural network,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
358 | 0925-2312 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Fang | 1 | 1 | 0.69 |
| Zhaofei Yu | 2 | 38 | 16.83 |
| Jian K. Liu | 3 | 20 | 8.77 |
| Feng Chen | 4 | 431 | 33.92 |