Moved things in assets/resources out to assets/

21 files changed, 19 insertions, 19 deletions

diff --git a/assets/resources/1423graph.jpg b/assets/1423graph.jpg
index 1a6e739..1a6e739 100644
--- a/assets/resources/1423graph.jpg
+++ b/assets/1423graph.jpg
diff --git a/assets/resources/dpmm.png b/assets/dpmm.png
index 7d41b41..7d41b41 100644
--- a/assets/resources/dpmm.png
+++ b/assets/dpmm.png
diff --git a/assets/resources/fully-bayesian-mm.png b/assets/fully-bayesian-mm.png
index 5ce98c8..5ce98c8 100644
--- a/assets/resources/fully-bayesian-mm.png
+++ b/assets/fully-bayesian-mm.png
diff --git a/assets/resources/hmm.png b/assets/hmm.png
index da902cc..da902cc 100644
--- a/assets/resources/hmm.png
+++ b/assets/hmm.png
diff --git a/assets/resources/juggling.png b/assets/juggling.png
index 18ec08b..18ec08b 100644
--- a/assets/resources/juggling.png
+++ b/assets/juggling.png
diff --git a/assets/resources/lda.png b/assets/lda.png
index 3eef014..3eef014 100644
--- a/assets/resources/lda.png
+++ b/assets/lda.png
diff --git a/assets/resources/mixture-model.png b/assets/mixture-model.png
index b0787a5..b0787a5 100644
--- a/assets/resources/mixture-model.png
+++ b/assets/mixture-model.png
diff --git a/assets/resources/plsa1.png b/assets/plsa1.png
index 8fa81a6..8fa81a6 100644
--- a/assets/resources/plsa1.png
+++ b/assets/plsa1.png
diff --git a/assets/resources/plsa2.png b/assets/plsa2.png
index 6b38829..6b38829 100644
--- a/assets/resources/plsa2.png
+++ b/assets/plsa2.png
diff --git a/assets/resources/qrsklatest.pdf b/assets/qrsklatest.pdf
index 01a042b..01a042b 100644
--- a/assets/resources/qrsklatest.pdf
+++ b/assets/qrsklatest.pdf
diff --git a/assets/resources/realdis.pdf b/assets/realdis.pdf
index 92d9302..92d9302 100644
--- a/assets/resources/realdis.pdf
+++ b/assets/realdis.pdf
diff --git a/assets/resources/sl-vs-ml.png b/assets/sl-vs-ml.png
index 11ad6a8..11ad6a8 100644
--- a/assets/resources/sl-vs-ml.png
+++ b/assets/sl-vs-ml.png
diff --git a/assets/resources/wangana.png b/assets/wangana.png
index b8457dc..b8457dc 100644
--- a/assets/resources/wangana.png
+++ b/assets/wangana.png
diff --git a/assets/resources/wangana_screenshot_index.png b/assets/wangana_screenshot_index.png
index ecaa8ac..ecaa8ac 100644
--- a/assets/resources/wangana_screenshot_index.png
+++ b/assets/wangana_screenshot_index.png
diff --git a/posts/2014-04-01-q-robinson-schensted-symmetry-paper.md b/posts/2014-04-01-q-robinson-schensted-symmetry-paper.md
index 38874bb..a0432c8 100644
--- a/posts/2014-04-01-q-robinson-schensted-symmetry-paper.md
+++ b/posts/2014-04-01-q-robinson-schensted-symmetry-paper.md
@@ -13,7 +13,7 @@ generalisation of the growth diagram approach introduced by Fomin. This
 approach, which uses "growth graphs", can also be applied to a wider
 class of insertion algorithms which have a branching structure.
 
-![Growth graph of q-RS for 1423](../assets/resources/1423graph.jpg)
+![Growth graph of q-RS for 1423](../assets/1423graph.jpg)
 
 Above is the growth graph of the \\(q\\)-weighted Robinson-Schensted
 algorithm for the permutation \\({1 2 3 4\\choose1 4 2 3}\\).
diff --git a/posts/2014-04-01-q-robinson-schensted-symmetry-paper.org b/posts/2014-04-01-q-robinson-schensted-symmetry-paper.org
index b1c967d..7411a5d 100644
--- a/posts/2014-04-01-q-robinson-schensted-symmetry-paper.org
+++ b/posts/2014-04-01-q-robinson-schensted-symmetry-paper.org
@@ -10,7 +10,7 @@ approach, which uses "growth graphs", can also be applied to a wider
 class of insertion algorithms which have a branching structure.
 
 #+caption: Growth graph of q-RS for 1423
-[[../assets/resources/1423graph.jpg]]
+[[../assets/1423graph.jpg]]
 
 Above is the growth graph of the \(q\)-weighted Robinson-Schensted
 algorithm for the permutation \({1 2 3 4\choose1 4 2 3}\).
diff --git a/posts/2015-04-02-juggling-skill-tree.md b/posts/2015-04-02-juggling-skill-tree.md
index 11eb377..7708988 100644
--- a/posts/2015-04-02-juggling-skill-tree.md
+++ b/posts/2015-04-02-juggling-skill-tree.md
@@ -30,4 +30,4 @@ have therefore written a script using [Python](http://python.org),
 difficulties, which is the leftmost column) from the Library of Juggling
 (click the image for the full size): 
 
-<a href="../assets/resources/juggling.png"><img src="../assets/resources/juggling.png" alt="The juggling skill tree" style="width:38em" /></a>
+<a href="../assets/juggling.png"><img src="../assets/juggling.png" alt="The juggling skill tree" style="width:38em" /></a>
diff --git a/posts/2016-10-13-q-robinson-schensted-knuth-polymer.md b/posts/2016-10-13-q-robinson-schensted-knuth-polymer.md
index 4d31e37..4a5f793 100644
--- a/posts/2016-10-13-q-robinson-schensted-knuth-polymer.md
+++ b/posts/2016-10-13-q-robinson-schensted-knuth-polymer.md
@@ -12,7 +12,7 @@ This article is available at [arXiv](https://arxiv.org/abs/1610.03692).
 It seems to me that one difference between arXiv and Github is that on arXiv each preprint has a few versions only.
 In Github many projects have a "dev" branch hosting continuous updates, whereas the master branch is where the stable releases live.
 
-[Here]({{ site.url }}/assets/resources/qrsklatest.pdf) is a "dev" version of the article, which I shall push to arXiv when it stablises. Below is the changelog.
+[Here]({{ site.url }}/assets/qrsklatest.pdf) is a "dev" version of the article, which I shall push to arXiv when it stablises. Below is the changelog.
 
 * 2017-01-12: Typos and grammar, arXiv v2.
 * 2016-12-20: Added remarks on the geometric \\(q\\)-pushTASEP. Added remarks on the converse of the Burke property. Added natural language description of the \\(q\\)RSK. Fixed typos.
diff --git a/posts/2016-10-13-q-robinson-schensted-knuth-polymer.org b/posts/2016-10-13-q-robinson-schensted-knuth-polymer.org
index 93da639..206a4ab 100644
--- a/posts/2016-10-13-q-robinson-schensted-knuth-polymer.org
+++ b/posts/2016-10-13-q-robinson-schensted-knuth-polymer.org
@@ -28,7 +28,7 @@ few versions only. In Github many projects have a "dev" branch hosting
 continuous updates, whereas the master branch is where the stable
 releases live.
 
-[[file:%7B%7B%20site.url%20%7D%7D/assets/resources/qrsklatest.pdf][Here]]
+[[file:/assets/qrsklatest.pdf][Here]]
 is a "dev" version of the article, which I shall push to arXiv when it
 stablises. Below is the changelog.
 
diff --git a/posts/2019-02-14-raise-your-elbo.md b/posts/2019-02-14-raise-your-elbo.md
index 4080d0b..36bd364 100644
--- a/posts/2019-02-14-raise-your-elbo.md
+++ b/posts/2019-02-14-raise-your-elbo.md
@@ -138,7 +138,7 @@ $p(x_{1 : m}; \theta)$.
 Represented as a DAG (a.k.a the plate notations), the model looks like
 this:
 
-![](/assets/resources/mixture-model.png){style="width:250px"}
+![](/assets/mixture-model.png){style="width:250px"}
 
 where the boxes with $m$ mean repitition for $m$ times, since there $m$
 indepdent pairs of $(x, z)$, and the same goes for $\eta$.
@@ -298,7 +298,7 @@ $$p(d_i = u, x_i = w | z_i = k; \theta) = p(d_i ; \xi_k) p(x_i; \eta_k) = \xi_{k
 
 The model can be illustrated in the plate notations:
 
-![](/assets/resources/plsa1.png){style="width:350px"}
+![](/assets/plsa1.png){style="width:350px"}
 
 So the solution of the M-step is
 
@@ -365,7 +365,7 @@ pLSA1, $(x | z = k) \sim \text{Cat}(\eta_{k, \cdot})$.
 
 Illustrated in the plate notations, pLSA2 is:
 
-![](/assets/resources/plsa2.png){style="width:350px"}
+![](/assets/plsa2.png){style="width:350px"}
 
 The computation is basically adding an index $\ell$ to the computation
 of SMM wherever applicable.
@@ -411,7 +411,7 @@ $$p(z_{i1}) = \pi_{z_{i1}}$$
 So the parameters are $\theta = (\pi, \xi, \eta)$. And HMM can be shown
 in plate notations as:
 
-![](/assets/resources/hmm.png){style="width:350px"}
+![](/assets/hmm.png){style="width:350px"}
 
 Now we apply EM to HMM, which is called the [Baum-Welch
 algorithm](https://en.wikipedia.org/wiki/Baum%E2%80%93Welch_algorithm).
@@ -569,7 +569,7 @@ later in this section that the posterior $q(\eta_k)$ belongs to the
 same family as $p(\eta_k)$. Represented in a plate notations, a fully
 Bayesian mixture model looks like:
 
-![](/assets/resources/fully-bayesian-mm.png){style="width:450px"}
+![](/assets/fully-bayesian-mm.png){style="width:450px"}
 
 Given this structure we can write down the mean-field approximation:
 
@@ -672,7 +672,7 @@ As the second example of fully Bayesian mixture models, Latent Dirichlet
 allocation (LDA) (Blei-Ng-Jordan 2003) is the fully Bayesian version of
 pLSA2, with the following plate notations:
 
-![](/assets/resources/lda.png){style="width:450px"}
+![](/assets/lda.png){style="width:450px"}
 
 It is the smoothed version in the paper.
 
@@ -782,7 +782,7 @@ $$L(p, q) = \sum_{k = 1 : T} \mathbb E_{q(\theta_k)} \log {p(\theta_k) \over q(\
 
 The plate notation of this model is:
 
-![](/assets/resources/dpmm.png){style="width:450px"}
+![](/assets/dpmm.png){style="width:450px"}
 
 As it turns out, the infinities can be tamed in this case.
 
diff --git a/posts/2019-02-14-raise-your-elbo.org b/posts/2019-02-14-raise-your-elbo.org
index f0de7d1..9cc79a7 100644
--- a/posts/2019-02-14-raise-your-elbo.org
+++ b/posts/2019-02-14-raise-your-elbo.org
@@ -137,7 +137,7 @@ $p(x_{1 : m}; \theta)$.
 Represented as a DAG (a.k.a the plate notations), the model looks like
 this:
 
-[[/assets/resources/mixture-model.png]]
+[[/assets/mixture-model.png]]
 
 where the boxes with $m$ mean repitition for $m$ times, since there $m$
 indepdent pairs of $(x, z)$, and the same goes for $\eta$.
@@ -309,7 +309,7 @@ $$p(d_i = u, x_i = w | z_i = k; \theta) = p(d_i ; \xi_k) p(x_i; \eta_k) = \xi_{k
 
 The model can be illustrated in the plate notations:
 
-[[/assets/resources/plsa1.png]]
+[[/assets/plsa1.png]]
 
 So the solution of the M-step is
 
@@ -380,7 +380,7 @@ pLSA1, $(x | z = k) \sim \text{Cat}(\eta_{k, \cdot})$.
 
 Illustrated in the plate notations, pLSA2 is:
 
-[[/assets/resources/plsa2.png]]
+[[/assets/plsa2.png]]
 
 The computation is basically adding an index $\ell$ to the computation
 of SMM wherever applicable.
@@ -429,7 +429,7 @@ $$p(z_{i1}) = \pi_{z_{i1}}$$
 So the parameters are $\theta = (\pi, \xi, \eta)$. And HMM can be shown
 in plate notations as:
 
-[[/assets/resources/hmm.png]]
+[[/assets/hmm.png]]
 
 Now we apply EM to HMM, which is called the
 [[https://en.wikipedia.org/wiki/Baum%E2%80%93Welch_algorithm][Baum-Welch
@@ -592,7 +592,7 @@ later in this section that the posterior $q(\eta_k)$ belongs to the same
 family as $p(\eta_k)$. Represented in a plate notations, a fully
 Bayesian mixture model looks like:
 
-[[/assets/resources/fully-bayesian-mm.png]]
+[[/assets/fully-bayesian-mm.png]]
 
 Given this structure we can write down the mean-field approximation:
 
@@ -701,7 +701,7 @@ As the second example of fully Bayesian mixture models, Latent Dirichlet
 allocation (LDA) (Blei-Ng-Jordan 2003) is the fully Bayesian version of
 pLSA2, with the following plate notations:
 
-[[/assets/resources/lda.png]]
+[[/assets/lda.png]]
 
 It is the smoothed version in the paper.
 
@@ -813,7 +813,7 @@ $$L(p, q) = \sum_{k = 1 : T} \mathbb E_{q(\theta_k)} \log {p(\theta_k) \over q(\
 
 The plate notation of this model is:
 
-[[/assets/resources/dpmm.png]]
+[[/assets/dpmm.png]]
 
 As it turns out, the infinities can be tamed in this case.