Deep Learning
Variational Structured Semantic Inference for Diverse Image Captioning
Fuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang, Yan Wang
Neural Information Processing Systems http://nips.cc/
A Statistical Recurrent Model on the Manifold of Symmetric Positive Definite Matrices
Rudrasis Chakraborty, Chun-Hao Yang, Xingjian Zhen, Monami Banerjee, Derek Archer, David Vaillancourt, Vikas Singh, Baba Vemuri
In a number of disciplines, the data (e.g., graphs, manifolds) to be analyzed are non-Euclideaninnature.
Image Inpainting via Generative Multi-column Convolutional Neural Networks
Yi Wang, Xin Tao, Xiaojuan Qi, Xiaoyong Shen, Jiaya Jia
In this paper, we propose a generative multi-column network for image inpainting.
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
Jiong Zhang, Hsiang-Fu Yu, Inderjit S. Dhillon
Neural Information Processing Systems http://nips.cc/
Deep Neural Nets with Interpolating Function as Output Activation
Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley Osher
And we propose end-to-end training and testing algorithms for this new architecture. Compared to classical neural nets with softmax function as output activation, the surrogate with interpolating function as output activation combines advantages of both deep and manifold learning.
