Neat papers in ML and DS: Dec 2018
- ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
- Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
NeurIPS
- Are GANs Created Equal? A Large-Scale Study
- An intriguing failing of convolutional neural networks and the CoordConv solution
- On the Dimensionality of Word Embedding
- Adversarial Examples that Fool both Computer Vision and Time-Limited Humans
- Bias and Generalization in Deep Generative Models: An Empirical Study
- How Does Batch Normalization Help Optimization?
- Training Deep Models Faster with Robust, Approximate Importance Sampling
- DropMax: Adaptive Variational Softmax
- Relational recurrent neural networks
- Neural Arithmetic Logic Units