Statistical Learning
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
Vincent Sitzmann, Michael Zollhoefer, Gordon Wetzstein
We propose Scene Representation Networks (SRNs), a continuous, 3D-structure-aware scene representation that encodes both geometry and appearance. SRNs represent scenes as continuous functions that map world coordinates to a feature representation of local scene properties.
Implicit Reparameterization Gradients
Mikhail Figurnov, Shakir Mohamed, Andriy Mnih
Neural Information Processing Systems http://nips.cc/
Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization
Yuanxiang Gao, Li Chen, Baochun Li
Neural Information Processing Systems http://nips.cc/
SplineNets: Continuous Neural Decision Graphs
Neural Information Processing Systems http://nips.cc/
Dual Variational Generation for Low Shot Heterogeneous Face Recognition
Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, Ran He
Neural Information Processing Systems http://nips.cc/
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
The number of features is comparable to the sample size and errors may be heavy-tailed.
Deep Active Learning with a Neural Architecture Search
Neural Information Processing Systems http://nips.cc/
