[1] 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data Maurice Weiler, Ma…
NIPS2018论文及代码集锦(29)(亮点：可逆卷积流模型;条件GANs;高斯过程先验变分自编码)
[1] Glow: Generative Flow with Invertible 1×1 Convolutions Diederik P. Kingma, Prafulla Dhariwal OpenAI…
NIPS2018论文及代码集锦(28)(亮点：人脸DepthNets;异常图像检测;循环动态模型)
[1] Unsupervised Depth Estimation, 3D Face Rotation and Replacement Joel Ruben Antony Moniz, Christophe…
NIPS2018论文及代码集锦(27)(亮点：对话推荐;协同坐标卷积;可逆卷积生成网络)
[1] An intriguing failing of convolutional neural networks and the CoordConv solution Rosanne Liu, Joel…
NIPS2018论文及代码集锦(26)(亮点：代表样本选择;上下文卷积网络;反馈编码)
[1] Representer Point Selection for Explaining Deep Neural Networks Chih-Kuan Yeh, Joon Sik Kim, Ian E.…
NIPS2018论文及代码集锦(25)(亮点：组胶囊网络;可逆RNN;动力学模型)
[1] Group Equivariant Capsule Networks Jan Eric Lenssen, Matthias Fey, Pascal Libuschewski TU Dortmund …
NIPS2018论文及代码集锦(24)(亮点：可复制特征选择;随意InfoGAN;快速融合)
[1] DeepPINK: reproducible feature selection in deep neural networks Yang Young Lu, Yingying Fan, Jinch…
NIPS2018论文及代码集锦(23)(亮点：RenderNet卷积网络;哈密顿变分自编码;co-teaching)
[1] RenderNet: A deep convolutional network for differentiable rendering from 3D shapes Thu Nguyen-Phuo…
NIPS2018论文及代码集锦(22)(亮点：深层高斯过程;变分自编码)
[1] Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo Marton Havasi, Jose…
NIPS2018论文及代码集锦(21)(亮点： 异常检测;强化学习)
[1] BRUNO: A Deep Recurrent Model for Exchangeable Data Iryna Korshunova, Jonas Degrave, Ferenc Huszár, Yarin …