This is a list papers that I’ve read with some summaries and implementation code. They are sorted in inverse chronological order with links to their respective arXiv page.
2018-04
2018-03
- Dimensionality Reduction by Learning an Invariant Mapping
- Siamese Neural Networks for One-shot Image Recognition
2018-02
2017-12
2017-09
2017-08
- Focal Loss for Dense Object Detection
- SGDR: Stochastic Gradient Descent With Warm Restarts
- FreezeOut: Accelerate Training By Progressively Freezing Layers
- Densely Connected Convolutional Networks
2017-06
- Learning to Reason: End-to-End Module Networks for Visual Question Answering
- Neural Module Networks
- Inferring and Executing Programs for Visual Reasoning
- Attention Is All You Need
- Learning To Diagnose With LSTM Recurrent Neural Networks
- Self-Normalizing Neural Networks
2017-05
2017-03
- Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
- Image-to-Image Translation with Conditional Adversarial Networks
- Generative Adversarial Nets
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
2017-01
- Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks
- Automatic Chemical Design using a Data-Driven Continuous Representation of Molecules
- Generating Sequences from a Continuous Space
2016-12
- Language Modeling with Gated Convolutional Networks
- Spatial Transformer Networks
- Perceptual Losses for Real-Time Style Transfer and Super-Resolution
2016-11
2016-10
2016-09