2.3k citations · 4.9k across the 9 of their papers we have counts for
9 papers
Importance Sampling BRDF Derivatives
Yash Belhe, Bing Xu, Sai Praveen Bangaru +2
We propose a set of techniques to efficiently importance sample the derivatives of several BRDF models. In differentiable rendering, BRDFs are replaced by their differential BRDF c…
Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images
Bingna Xu, Yong Guo, Luoqian Jiang +2
Deep networks have achieved great success in image rescaling (IR) task that seeks to learn the optimal downscaled representations, i.e., low-resolution (LR) images, to reconstruct…
Hybrid Composition with IdleBlock: More Efficient Networks for Image Recognition
Bing Xu, Andrew Tulloch, Yunpeng Chen +2
We propose a new building block, IdleBlock, which naturally prunes connections within the block. To fully utilize the IdleBlock we break the tradition of monotonic design in state-…
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Yunpeng Chen, Haoqi Fan, Bing Xu +5
In natural images, information is conveyed at different frequencies where higher frequencies are usually encoded with fine details and lower frequencies are usually encoded with gl…
Training Deep Nets with Sublinear Memory Cost
Tianqi Chen, Bing Xu, Chiyuan Zhang +1
We propose a systematic approach to reduce the memory consumption of deep neural network training. Specifically, we design an algorithm that costs O(sqrt(n)) memory to train a n la…
Revise Saturated Activation Functions
Bing Xu, Ruitong Huang, Mu Li
In this paper, we revise two commonly used saturated functions, the logistic sigmoid and the hyperbolic tangent (tanh). We point out that, besides the well-known non-zero centered…
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
Tianqi Chen, Mu Li, Yutian Li +7
MXNet is a multi-language machine learning (ML) library to ease the development of ML algorithms, especially for deep neural networks. Embedded in the host language, it blends decl…
Empirical Evaluation of Rectified Activations in Convolutional Network
Bing Xu, Naiyan Wang, Tianqi Chen +1
In this paper we investigate the performance of different types of rectified activation functions in convolutional neural network: standard rectified linear unit (ReLU), leaky rect…
Horizontal and Vertical Ensemble with Deep Representation for Classification
Jingjing Xie, Bing Xu, Zhang Chuang
Representation learning, especially which by using deep learning, has been widely applied in classification. However, how to use limited size of labeled data to achieve good classi…