Updating section on Papers by Google X

yml-blog · Jul 8, 2019 · a091f2b · a091f2b
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diff --git a/README-details.md b/README-details.md
@@ -381,7 +381,7 @@ See [Visualisation](README-details.md#visualisation-1)
   - [Data.world's open data - catalog your data, wake up your hidden data workforce, and build a data-driven culture—faster](https://data.world/)
   - [Browse state-of-the-art](https://paperswithcode.com/sota)
   - [ML/DL/Data Science resources (scattered across the page)](https://github.com/ayonroy2000/100DaysOfML_TelegramGroup/blob/master/Resources.md)
-  - [Papers by Google X](./papers/google-x/README.md)
+  - [Papers by Google X](./papers/google-x/README.md#papers-by-members-of-google-and-google-x-aka-x-team)
   - [NLP presentations](./natural-language-processing/README.md#presentations)
     - [Better NLP - presentations](./examples/better-nlp/presentations)
   - [Data presentations](./presentations/data/)

diff --git a/README.md b/README.md
@@ -52,7 +52,7 @@ Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn
   - [Time-series / anomaly detection](time-series_anomaly-detection/README.md)
   - [Notebooks](README-details.md#notebooks)
   - [Models](README-details.md#models)
-  - [Articles, papers, code, data, courses](README-details.md#articles-papers-code-data)
+  - [Articles, papers, code, data, courses](./README-details.md#articles-papers-code-data-courses-presentations)
   - [Cheatsheets](README-details.md#cheatsheets)
   - [Misc](README-details.md#misc-1)
 - [Contributing](#contributing)

diff --git a/papers/google-x/README.md b/papers/google-x/README.md
@@ -1,18 +1,26 @@
-## Papers by Google X 
+## Papers by members of Google and Google X (aka X-Team)
 
-- [Page 01 - Abstract (Tensor Network).jpg](./papers/google-x/Page\ 01\ -\ Abstract\ \(Tensor\ Network\).jpg)
-- [Page 02 - What is a Tensor network.jpg](./papers/google-x/Page\ 02\ -\ What\ is\ a\ Tensor\ network.jpg)
-- [Page 03 - What is a Tensor network.jpg](./papers/google-x/Page\ 03\ -\ What\ is\ a\ Tensor\ network.jpg)
-- [Page 04 - A tree Tensor network....jpg](./papers/google-x/Page\ 04\ -\ A\ tree\ Tensor\ network....jpg)
-- [Page 05 - Tensor Network - a library for ...jpg](./papers/google-x/Page\ 05\ -\ Tensor\ Network\ -\ a\ library\ for\ ...jpg)
-- [Page 06 - Generalisation & no overfitting - Abstract.jpg](./papers/google-x/Page\ 06\ -\ Generalisation\ \&\ no\ overfitting\ -\ Abstract.jpg)
-- [Page 07 - Generalisation & no overfitting.jpg](./papers/google-x/Page\ 07\ -\ Generalisation\ \&\ no\ overfitting.jpg)
-- [Page 08 - Dynamical systems and Deep nets.jpg](./papers/google-x/Page\ 08\ -\ Dynamical\ systems\ and\ Deep\ nets.jpg)
-- [Page 09 - Generalisation bounds.jpg](./papers/google-x/Page\ 09\ -\ Generalisation\ bounds.jpg)
-- [Page 10 - Norm-minimising Gradient descent.jpg](./papers/google-x/Page\ 10\ -\ Norm-minimising\ Gradient\ descent.jpg)
-- [Page 11 - Norm-minimising Gradient descent.jpg](./papers/google-x/Page\ 11\ -\ Norm-minimising\ Gradient\ descent.jpg)
-- [Page 12 - Comparing BN and WN.jpg](./papers/google-x/Page\ 12\ -\ Comparing\ BN\ and\ WN.jpg)
-- [Page 13 - Ranking Minimas.jpg](./papers/google-x/Page\ 13\ -\ Ranking\ Minimas.jpg)
-- [Page 14 - Contributions to Science & Engineering of Intelligence.jpg](./papers/google-x/Page\ 14\ -\ Contributions\ to\ Science\ \&\ Engineering\ of\ Intelligence.jpg)
+- [TensorNetwork for Machine Learning](https://arxiv.org/pdf/1906.06329.pdf) 
+- [Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping](https://arxiv.org/abs/1709.07857)
+- [QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation](https://arxiv.org/abs/1806.10293)
+- [Theory III: Dynamics and Generalization in Deep Networks -- a simple solution](https://arxiv.org/abs/1903.04991)
+- [A Surprising Linear Relationship Predicts Test Performance in Deep Networks](https://arxiv.org/abs/1807.09659)
+- [TensorNetwork: A Library for Physics and Machine Learning](https://arxiv.org/abs/1905.01330) | [library](https://github.com/google/tensornetwork)
+- [TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor Networks](https://arxiv.org/abs/1905.01331) | [library](https://github.com/google/tensornetwork)
+- Pictures of some aspects of the above papers
+    - [Page 01 - Abstract (Tensor Network).jpg](./papers/google-x/Page\ 01\ -\ Abstract\ \(Tensor\ Network\).jpg)
+    - [Page 02 - What is a Tensor network.jpg](./papers/google-x/Page\ 02\ -\ What\ is\ a\ Tensor\ network.jpg)
+    - [Page 03 - What is a Tensor network.jpg](./papers/google-x/Page\ 03\ -\ What\ is\ a\ Tensor\ network.jpg)
+    - [Page 04 - A tree Tensor network....jpg](./papers/google-x/Page\ 04\ -\ A\ tree\ Tensor\ network....jpg)
+    - [Page 05 - Tensor Network - a library for ...jpg](./papers/google-x/Page\ 05\ -\ Tensor\ Network\ -\ a\ library\ for\ ...jpg)
+    - [Page 06 - Generalisation & no overfitting - Abstract.jpg](./papers/google-x/Page\ 06\ -\ Generalisation\ \&\ no\ overfitting\ -\ Abstract.jpg)
+    - [Page 07 - Generalisation & no overfitting.jpg](./papers/google-x/Page\ 07\ -\ Generalisation\ \&\ no\ overfitting.jpg)
+    - [Page 08 - Dynamical systems and Deep nets.jpg](./papers/google-x/Page\ 08\ -\ Dynamical\ systems\ and\ Deep\ nets.jpg)
+    - [Page 09 - Generalisation bounds.jpg](./papers/google-x/Page\ 09\ -\ Generalisation\ bounds.jpg)
+    - [Page 10 - Norm-minimising Gradient descent.jpg](./papers/google-x/Page\ 10\ -\ Norm-minimising\ Gradient\ descent.jpg)
+    - [Page 11 - Norm-minimising Gradient descent.jpg](./papers/google-x/Page\ 11\ -\ Norm-minimising\ Gradient\ descent.jpg)
+    - [Page 12 - Comparing BN and WN.jpg](./papers/google-x/Page\ 12\ -\ Comparing\ BN\ and\ WN.jpg)
+    - [Page 13 - Ranking Minimas.jpg](./papers/google-x/Page\ 13\ -\ Ranking\ Minimas.jpg)
+    - [Page 14 - Contributions to Science & Engineering of Intelligence.jpg](./papers/google-x/Page\ 14\ -\ Contributions\ to\ Science\ \&\ Engineering\ of\ Intelligence.jpg)
 
-Back to [main page (table of contents)](../README.md)
+Back to [main page (table of contents)](../../README.md)