- Dirichlet Processes And Friends with Ryan Adams: https://www.youtube.com/watch?v=xusN7RqKpPI (Sydney MLSS 2015)
- New Papers Dividing Logical Uncertainty into Two Subproblems: https://intelligence.org/2016/04/21/two-new-papers-uniform/
- Sorry ARIMA, But I’m Going Bayesian: http://multithreaded.stitchfix.com/blog/2016/04/21/forget-arima/
- Neural Networks to Upscale & Stylize Pixel Art: https://nucl.ai/blog/enhance-pixel-art/
- Generative Choreography: http://peltarion.com/creative-ai
- The Master Algorithm: http://blog.computationalcomplexity.org/2016/04/the-master-algorithm.html
- This Week in ML: http://i.imgur.com/9fLbZxl.png
- TensorFlow Introductory Lecture: https://www.reddit.com/r/MachineLearning/comments/4fwnjf/tensorflow_introductory_lecture/
- Wikipedia Exploring with Machine Learning Chrome Extension: https://chrome.google.com/webstore/detail/similar-pages-for-wikiped/ibabphmjpolljfillmhiikhdohbolado
- Doom AI Competition: http://vizdoom.cs.put.edu.pl/competition-cig-2016
- Training Deep Nets with Sublinear Memory Cost: https://arxiv.org/abs/1604.06174
- The Amazing Power of Word Vectors: https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/
- Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation: http://arxiv.org/abs/1604.06057
- DenseCap: Fully Convolutional Localization Networks for Dense Captioning: http://cs.stanford.edu/people/karpathy/densecap/
- Backpropogating an LSTM: A Numerical Example: https://blog.aidangomez.ca/2016/04/17/Backpropogating-an-LSTM-A-Numerical-Example/
- ML Meets Economics, Part 2: http://blog.mldb.ai/blog/posts/2016/04/ml-meets-economics2/
- Visualization of Different Classification Algorithms: http://haifengl.github.io/smile/index.html#classification
- Course on Deep Learning by joanbruna: http://joanbruna.github.io/stat212b/
- Short Science, Summary Sharing Service for Academic Papers: http://www.shortscience.org/about
- What ConvNets See When It Sees Nudity: http://blog.clarifai.com/what-convolutional-neural-networks-see-at-when-they-see-nudity/#.Vx1i8Pl95hF
- Bridging the Gaps Between Residual Learning, RNNs, and Visual Cortex: http://arxiv.org/abs/1604.03640v1
- Training A Big Data Machine to Defend: http://people.csail.mit.edu/kalyan/AI2_Paper.pdf
- Futhark Programming Language – High-Performance Purely Functional Data-parallel Array Programming on the GPU: http://futhark-lang.org//
- Improving the Robustness of Deep Neural Networks via Stability Training: http://arxiv.org/abs/1604.04326
- CondensedLectures – Stanford Machine Learning Lecture 2: https://www.youtube.com/watch?v=n8LXeHUNeXg
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