diff options
Diffstat (limited to '')
-rw-r--r-- | documentation/research/machine_learning.md | 67 |
1 files changed, 67 insertions, 0 deletions
diff --git a/documentation/research/machine_learning.md b/documentation/research/machine_learning.md new file mode 100644 index 000000000..6a46367da --- /dev/null +++ b/documentation/research/machine_learning.md @@ -0,0 +1,67 @@ +# Exemplar + +1. https://ml5js.org/ +1. https://www.csie.ntu.edu.tw/~cjlin/libsvm/ +1. http://halide-lang.org/ + +# Reference + +1. [HyperE: Hyperbolic Embeddings for Entities](https://hazyresearch.github.io/hyperE/) +1. https://www.samcoope.com/posts/playing_around_with_noise_as_targets +1. https://lobste.rs/s/hgejxf/why_is_machine_learning_most_often +1. https://boingboing.net/2018/11/12/local-optima-r-us.html/amp +1. https://crazyoscarchang.github.io/2019/02/16/seven-myths-in-machine-learning-research/ +1. https://www.c4ml.org/ +1. https://medium.com/@l2k/why-are-machine-learning-projects-so-hard-to-manage-8e9b9cf49641 +1. https://github.com/MikeInnes/diff-zoo +1. https://cloud.google.com/blog/products/ai-machine-learning/introducing-feast-an-open-source-feature-store-for-machine-learning +1. https://towardsdatascience.com/introducing-manifold-db9e90f20347 +1. http://snap.stanford.edu/graphsage/ +1. https://heartbeat.fritz.ai/capsule-networks-a-new-and-attractive-ai-architecture-bd1198cc8ad4 +1. http://super-ms.mit.edu/rum.html + +# Deep learning + +1. https://d2l.ai/ +1. https://hadrienj.github.io/posts/Deep-Learning-Book-Series-Introduction/ +1. http://nlp.seas.harvard.edu/NamedTensor +1. https://tvm.ai/ +1. https://machinelearningmastery.com/framework-for-better-deep-learning/ +1. [Geometric Understanding of Deep Learning](https://arxiv.org/abs/1805.10451) +1. https://towardsdatascience.com/what-is-geometric-deep-learning-b2adb662d91d +1. https://deeplearning4j.org/ +1. [Deep(er) learning](http://www.jneurosci.org/content/early/2018/07/13/JNEUROSCI.0153-18.2018?versioned=true) + +# Neural network + +1. https://github.com/BrainJS/brain.js +1. https://blog.jle.im/entry/practical-dependent-types-in-haskell-1.html +1. https://matloff.wordpress.com/2018/06/20/neural-networks-are-essentially-polynomial-regression/ +1. https://www.quantamagazine.org/foundations-built-for-a-general-theory-of-neural-networks-20190131#AI +1. https://rkevingibson.github.io/blog/neural-networks-as-ordinary-differential-equations/ + +# Tensor + +1. http://nlp.seas.harvard.edu/NamedTensor.html +1. http://nlp.seas.harvard.edu/NamedTensor2 + +# Meta-learning + +1. https://www.bayeswatch.com/2018/11/30/HTYM/ +1. https://bender.dreem.com/ + +# Model + +1. http://onnx.ai/ + +# Training + +1. https://ai.googleblog.com/2019/03/introducing-gpipe-open-source-library.html + +# Differentiable programming + +1. https://fluxml.ai/2019/02/07/what-is-differentiable-programming.html +1. https://github.com/breandan/kotlingrad +1. https://colinraffel.com/blog/you-don-t-know-jax.html +1. https://github.com/tensorflow/mlir + |