7 citations · 34 across the 10 of their papers we have counts for
10 papers
Relating Human Perception of Musicality to Prediction in a Predictive Coding Model
Nikolas McNeal, Jennifer Huang, Aniekan Umoren +4
We explore the use of a neural network inspired by predictive coding for modeling human music perception. This network was developed based on the computational neuroscience theory…
SurfGen: Adversarial 3D Shape Synthesis with Explicit Surface Discriminators
Andrew Luo, Tianqin Li, Wen-Hao Zhang +1
Recent advances in deep generative models have led to immense progress in 3D shape synthesis. While existing models are able to synthesize shapes represented as voxels, point-cloud…
Recurrent networks improve neural response prediction and provide insights into underlying cortical circuits
Yimeng Zhang, Harold Rockwell, Sicheng Dai +4
Feedforward CNN models have proven themselves in recent years as state-of-the-art models for predicting single-neuron responses to natural images in early visual cortical neurons.…
Recurrent Feedback Improves Feedforward Representations in Deep Neural Networks
Siming Yan, Xuyang Fang, Bowen Xiao +3
The abundant recurrent horizontal and feedback connections in the primate visual cortex are thought to play an important role in bringing global and semantic contextual information…
A Neurally-Inspired Hierarchical Prediction Network for Spatiotemporal Sequence Learning and Prediction
Jielin Qiu, Ge Huang, Tai Sing Lee
In this paper we developed a hierarchical network model, called Hierarchical Prediction Network (HPNet), to understand how spatiotemporal memories might be learned and encoded in t…
Learning to Associate Words and Images Using a Large-scale Graph
Heqing Ya, Haonan Sun, Jeffrey Helt +1
We develop an approach for unsupervised learning of associations between co-occurring perceptual events using a large graph. We applied this approach to successfully solve the imag…