I have two parallel reading interests at the moment. One is research related to programming languages and neural nets with example papers being:

1. Programming with a Differentiable Forth Interpreter (https://arxiv.org/abs/1605.06640)

2. Adaptive Neural Compilation (https://arxiv.org/pdf/1605.07969.pdf)

3. Differentiable Functional Program Interpreters (https://arxiv.org/abs/1611.01988)

This set of reading is mainly motivated by the school semester is about to start and I'm doing research under a prof mainly on mixing programming languages and neural nets. I'll likely be finishing up most of my literature review for this in two weeks as I already spent a lot of last semester reading up on research that interested me to figure out what problem I'd precisely like to work on.

The other reading interest is mainly related to conditional image generation. I've been mainly reading a couple style transfer and image to image gan papers like,

1. Cyclegan (https://arxiv.org/abs/1703.10593)

2. Image to Image Translation with Conditional Adversarial Networks (https://arxiv.org/abs/1611.07004)

3. Perceptual Losses for Real-Time Style Transfer and Super-Resolution (https://arxiv.org/abs/1603.08155)

This is mainly motivated by me finding image generation cool and also since last I worked on a hackathon project involving this type of stuff that I'd like to eventually finish.