📚 Add clarification about how to read multi_aso() matrix, add "hall o…

…f fame" about papers using the package

README.md

@@ -22,6 +22,7 @@
   * [General Recommendations & other notes](#general-recommendations) 
 * [:mortar_board: Cite](#mortar_board-cite)
 * [:medal_sports: Acknowledgements](#medal_sports-acknowledgements)
+* [:people_holding_hands: Papers using deep-significance](#people_holding_hands-papers-using-deep-significance)
 * [:books: Bibliography](#books-bibliography)
 
 ### :interrobang: Why?
@@ -261,7 +262,9 @@ eps_min = multi_aso(my_models_scores, confidence_level=0.05)
 ```
 
 In the example, `eps_min` is now a matrix, containing the <img src="svgs/70bcb72c245ba47b6fc7439da91ec6fc.svg?invert_in_darkmode" align=middle width=28.45332764999999pt height=14.15524440000002pt/> score between all pairs of models (for 
-the same model, it set to 1 by default). The function applies the bonferroni correction for multiple comparisons by 
+the same model, it set to 1 by default). The matrix is always to be read as ASO(row, column).
+
+The function applies the bonferroni correction for multiple comparisons by 
 default, but this can be turned off by using `use_bonferroni=False`. In order to save compute, the above symmetry
 property is used as well, but this can also be disabled by `use_symmetry=False`.
 
@@ -441,6 +444,14 @@ answer questions and provide feedback to the implementation and documentation of
 The commit message template used in this project can be found [here](https://github.com/Kaleidophon/commit-template-for-humans).
 The inline latex equations were rendered using [readme2latex](https://github.com/leegao/readme2tex).
 
+### :people_holding_hands: Papers using deep-significance
+
+In this last section of the readme, I would like to refer to works already using `deep-significance`. Open an issue or 
+pull request if you would like to see your work added here!
+
+* ["From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding" (van der Groot et al., 2021)](https://robvanderg.github.io/doc/naacl2021.pdf)
+* ["Cartography Active Learning" (Zhang & Plank, 2021)](https://arxiv.org/pdf/2109.04282.pdf)
+
 ### :books: Bibliography
 
 Del Barrio, Eustasio, Juan A. Cuesta-Albertos, and Carlos Matrán. "An optimal transportation approach for assessing almost stochastic order." The Mathematics of the Uncertain. Springer, Cham, 2018. 33-44.

README_RAW.md

@@ -22,6 +22,7 @@
   * [General Recommendations & other notes](#general-recommendations) 
 * [:mortar_board: Cite](#mortar_board-cite)
 * [:medal_sports: Acknowledgements](#medal_sports-acknowledgements)
+* [:people_holding_hands: Papers using deep-significance](#people_holding_hands-papers-using-deep-significance)
 * [:books: Bibliography](#books-bibliography)
 
 ### :interrobang: Why?
@@ -271,7 +272,9 @@ eps_min = multi_aso(my_models_scores, confidence_level=0.05)
 ```
 
 In the example, `eps_min` is now a matrix, containing the $\epsilon_\text{min}$ score between all pairs of models (for 
-the same model, it set to 1 by default). The function applies the bonferroni correction for multiple comparisons by 
+the same model, it set to 1 by default). The matrix is always to be read as ASO(row, column).
+
+The function applies the bonferroni correction for multiple comparisons by 
 default, but this can be turned off by using `use_bonferroni=False`. In order to save compute, the above symmetry
 property is used as well, but this can also be disabled by `use_symmetry=False`.
 
@@ -451,6 +454,14 @@ answer questions and provide feedback to the implementation and documentation of
 The commit message template used in this project can be found [here](https://github.com/Kaleidophon/commit-template-for-humans).
 The inline latex equations were rendered using [readme2latex](https://github.com/leegao/readme2tex).
 
+### :people_holding_hands: Papers using deep-significance
+
+In this last section of the readme, I would like to refer to works already using `deep-significance`. Open an issue or 
+pull request if you would like to see your work added here!
+
+* ["From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding" (van der Groot et al., 2021)](https://robvanderg.github.io/doc/naacl2021.pdf)
+* ["Cartography Active Learning" (Zhang & Plank, 2021)](https://arxiv.org/pdf/2109.04282.pdf)
+
 ### :books: Bibliography
 
 Del Barrio, Eustasio, Juan A. Cuesta-Albertos, and Carlos Matrán. "An optimal transportation approach for assessing almost stochastic order." The Mathematics of the Uncertain. Springer, Cham, 2018. 33-44.

docs/README_DOCS.md

@@ -22,6 +22,7 @@
   * [General Recommendations & other notes](#general-recommendations) 
 * [|:mortar_board:| Cite](#mortar_board-cite)
 * [|:medal_sports:| Acknowledgements](#medal_sports-acknowledgements)
+* [|:people_holding_hands:| Papers using deep-significance](#people_holding_hands-papers-using-deep-significance)
 * [|:books:| Bibliography](#books-bibliography)
 
 ### |:interrobang:| Why?
@@ -261,7 +262,9 @@ eps_min = multi_aso(my_models_scores, confidence_level=0.05)
 ```
 
 In the example, `eps_min` is now a matrix, containing the <img src="70bcb72c245ba47b6fc7439da91ec6fc.svg?invert_in_darkmode" align=middle width=28.45332764999999pt height=14.15524440000002pt/> score between all pairs of models (for 
-the same model, it set to 1 by default). The function applies the bonferroni correction for multiple comparisons by 
+the same model, it set to 1 by default). The matrix is always to be read as ASO(row, column).
+
+The function applies the bonferroni correction for multiple comparisons by 
 default, but this can be turned off by using `use_bonferroni=False`. In order to save compute, the above symmetry
 property is used as well, but this can also be disabled by `use_symmetry=False`.
 
@@ -441,6 +444,14 @@ answer questions and provide feedback to the implementation and documentation of
 The commit message template used in this project can be found [here](https://github.com/Kaleidophon/commit-template-for-humans).
 The inline latex equations were rendered using [readme2latex](https://github.com/leegao/readme2tex).
 
+### |:people_holding_hands:| Papers using deep-significance
+
+In this last section of the readme, I would like to refer to works already using `deep-significance`. Open an issue or 
+pull request if you would like to see your work added here!
+
+* ["From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding" (van der Groot et al., 2021)](https://robvanderg.github.io/doc/naacl2021.pdf)
+* ["Cartography Active Learning" (Zhang & Plank, 2021)](https://arxiv.org/pdf/2109.04282.pdf)
+
 ### |:books:| Bibliography
 
 Del Barrio, Eustasio, Juan A. Cuesta-Albertos, and Carlos Matrán. "An optimal transportation approach for assessing almost stochastic order." The Mathematics of the Uncertain. Springer, Cham, 2018. 33-44.

docs/build/html/README_DOCS.html

@@ -114,6 +114,7 @@ <h4>Table Of Contents</h4>
 <li><a class="reference internal" href="#general-recommendations-other-notes">General recommendations &amp; other notes</a></li>
 <li><a class="reference internal" href="#mortar-board-cite">|:mortar_board:| Cite</a></li>
 <li><a class="reference internal" href="#medal-sports-acknowledgements">|:medal_sports:| Acknowledgements</a></li>
+<li><a class="reference internal" href="#people-holding-hands-papers-using-deep-significance">|:people_holding_hands:| Papers using deep-significance</a></li>
 <li><a class="reference internal" href="#books-bibliography">|:books:| Bibliography</a></li>
 </ul>
 </li>
@@ -170,6 +171,7 @@ <h1>deep-significance: Easy and Better Significance Testing for Deep Neural Netw
 </li>
 <li><p><a class="reference external" href="#mortar_board-cite">|:mortar_board:| Cite</a></p></li>
 <li><p><a class="reference external" href="#medal_sports-acknowledgements">|:medal_sports:| Acknowledgements</a></p></li>
+<li><p><a class="reference external" href="#people_holding_hands-papers-using-deep-significance">|:people_holding_hands:| Papers using deep-significance</a></p></li>
 <li><p><a class="reference external" href="#books-bibliography">|:books:| Bibliography</a></p></li>
 </ul>
 <div class="section" id="interrobang-why">
@@ -369,7 +371,8 @@ <h3>Scenario 4 - Comparing more than two models<a class="headerlink" href="#scen
 </pre></div>
 </div>
 <p>In the example, <code class="docutils literal notranslate"><span class="pre">eps_min</span></code> is now a matrix, containing the <img src="70bcb72c245ba47b6fc7439da91ec6fc.svg?invert_in_darkmode" align=middle width=28.45332764999999pt height=14.15524440000002pt/> score between all pairs of models (for
-the same model, it set to 1 by default). The function applies the bonferroni correction for multiple comparisons by
+the same model, it set to 1 by default). The matrix is always to be read as ASO(row, column).</p>
+<p>The function applies the bonferroni correction for multiple comparisons by
 default, but this can be turned off by using <code class="docutils literal notranslate"><span class="pre">use_bonferroni=False</span></code>. In order to save compute, the above symmetry
 property is used as well, but this can also be disabled by <code class="docutils literal notranslate"><span class="pre">use_symmetry=False</span></code>.</p>
 <p>Lastly, when the <code class="docutils literal notranslate"><span class="pre">scores</span></code> argument is a dictionary and the function is called with <code class="docutils literal notranslate"><span class="pre">return_df=True</span></code>, the resulting matrix is
@@ -544,6 +547,15 @@ <h3>|:medal_sports:| Acknowledgements<a class="headerlink" href="#medal-sports-a
 <p>The commit message template used in this project can be found <a class="reference external" href="https://github.com/Kaleidophon/commit-template-for-humans">here</a>.
 The inline latex equations were rendered using <a class="reference external" href="https://github.com/leegao/readme2tex">readme2latex</a>.</p>
 </div>
+<div class="section" id="people-holding-hands-papers-using-deep-significance">
+<h3>|:people_holding_hands:| Papers using deep-significance<a class="headerlink" href="#people-holding-hands-papers-using-deep-significance" title="Permalink to this headline">¶</a></h3>
+<p>In this last section of the readme, I would like to refer to works already using <code class="docutils literal notranslate"><span class="pre">deep-significance</span></code>. Open an issue or
+pull request if you would like to see your work added here!</p>
+<ul class="simple">
+<li><p><a class="reference external" href="https://robvanderg.github.io/doc/naacl2021.pdf">“From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding” (van der Groot et al., 2021)</a></p></li>
+<li><p><a class="reference external" href="https://arxiv.org/pdf/2109.04282.pdf">“Cartography Active Learning” (Zhang &amp; Plank, 2021)</a></p></li>
+</ul>
+</div>
 <div class="section" id="books-bibliography">
 <h3>|:books:| Bibliography<a class="headerlink" href="#books-bibliography" title="Permalink to this headline">¶</a></h3>
 <p>Del Barrio, Eustasio, Juan A. Cuesta-Albertos, and Carlos Matrán. “An optimal transportation approach for assessing almost stochastic order.” The Mathematics of the Uncertain. Springer, Cham, 2018. 33-44.</p>

docs/build/html/_sources/README_DOCS.md.txt

@@ -22,6 +22,7 @@
   * [General Recommendations & other notes](#general-recommendations) 
 * [|:mortar_board:| Cite](#mortar_board-cite)
 * [|:medal_sports:| Acknowledgements](#medal_sports-acknowledgements)
+* [|:people_holding_hands:| Papers using deep-significance](#people_holding_hands-papers-using-deep-significance)
 * [|:books:| Bibliography](#books-bibliography)
 
 ### |:interrobang:| Why?
@@ -261,7 +262,9 @@ eps_min = multi_aso(my_models_scores, confidence_level=0.05)
 ```
 
 In the example, `eps_min` is now a matrix, containing the <img src="70bcb72c245ba47b6fc7439da91ec6fc.svg?invert_in_darkmode" align=middle width=28.45332764999999pt height=14.15524440000002pt/> score between all pairs of models (for 
-the same model, it set to 1 by default). The function applies the bonferroni correction for multiple comparisons by 
+the same model, it set to 1 by default). The matrix is always to be read as ASO(row, column).
+
+The function applies the bonferroni correction for multiple comparisons by 
 default, but this can be turned off by using `use_bonferroni=False`. In order to save compute, the above symmetry
 property is used as well, but this can also be disabled by `use_symmetry=False`.
 
@@ -441,6 +444,14 @@ answer questions and provide feedback to the implementation and documentation of
 The commit message template used in this project can be found [here](https://github.com/Kaleidophon/commit-template-for-humans).
 The inline latex equations were rendered using [readme2latex](https://github.com/leegao/readme2tex).
 
+### |:people_holding_hands:| Papers using deep-significance
+
+In this last section of the readme, I would like to refer to works already using `deep-significance`. Open an issue or 
+pull request if you would like to see your work added here!
+
+* ["From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding" (van der Groot et al., 2021)](https://robvanderg.github.io/doc/naacl2021.pdf)
+* ["Cartography Active Learning" (Zhang & Plank, 2021)](https://arxiv.org/pdf/2109.04282.pdf)
+
 ### |:books:| Bibliography
 
 Del Barrio, Eustasio, Juan A. Cuesta-Albertos, and Carlos Matrán. "An optimal transportation approach for assessing almost stochastic order." The Mathematics of the Uncertain. Springer, Cham, 2018. 33-44.

docs/build/html/index.html

@@ -110,7 +110,8 @@ <h4>Table Of Contents</h4>
 <li><a class="reference internal" href="#id12">General recommendations &amp; other notes</a></li>
 <li><a class="reference internal" href="#id13">🎓 Cite</a></li>
 <li><a class="reference internal" href="#id14">🏅 Acknowledgements</a></li>
-<li><a class="reference internal" href="#id17">📚 Bibliography</a></li>
+<li><a class="reference internal" href="#id17">🧑‍🤝‍🧑 Papers using deep-significance</a></li>
+<li><a class="reference internal" href="#id18">📚 Bibliography</a></li>
 </ul>
 </li>
 <li><a class="reference internal" href="#module-deepsig">Documentation</a></li>
@@ -163,6 +164,7 @@ <h1>deep-significance: Easy and Better Significance Testing for Deep Neural Netw
 </li>
 <li><p><a class="reference external" href="#mortar_board-cite">|:mortar_board:| Cite</a></p></li>
 <li><p><a class="reference external" href="#medal_sports-acknowledgements">|:medal_sports:| Acknowledgements</a></p></li>
+<li><p><a class="reference external" href="#people_holding_hands-papers-using-deep-significance">|:people_holding_hands:| Papers using deep-significance</a></p></li>
 <li><p><a class="reference external" href="#books-bibliography">|:books:| Bibliography</a></p></li>
 </ul>
 <div class="section" id="id1">
@@ -363,7 +365,8 @@ <h2>Scenario 4 - Comparing more than two models<a class="headerlink" href="#id9"
 </pre></div>
 </div>
 <p>In the example, <code class="docutils literal notranslate"><span class="pre">eps_min</span></code> is now a matrix, containing the <span class="raw-html-m2r"><img src="70bcb72c245ba47b6fc7439da91ec6fc.svg?invert_in_darkmode" align=middle width=28.45332764999999pt height=14.15524440000002pt/></span> score between all pairs of models (for
-the same model, it set to 1 by default). The function applies the bonferroni correction for multiple comparisons by
+the same model, it set to 1 by default). The matrix is always to be read as ASO(row, column).</p>
+<p>The function applies the bonferroni correction for multiple comparisons by
 default, but this can be turned off by using <code class="docutils literal notranslate"><span class="pre">use_bonferroni=False</span></code>. In order to save compute, the above symmetry
 property is used as well, but this can also be disabled by <code class="docutils literal notranslate"><span class="pre">use_symmetry=False</span></code>.</p>
 <p>Lastly, when the <code class="docutils literal notranslate"><span class="pre">scores</span></code> argument is a dictionary and the function is called with <code class="docutils literal notranslate"><span class="pre">return_df=True</span></code>, the resulting matrix is
@@ -527,7 +530,16 @@ <h2>🏅 Acknowledgements<a class="headerlink" href="#id14" title="Permalink to
 The inline latex equations were rendered using <a class="reference external" href="https://github.com/leegao/readme2tex">readme2latex</a>.</p>
 </div>
 <div class="section" id="id17">
-<h2>📚 Bibliography<a class="headerlink" href="#id17" title="Permalink to this headline">¶</a></h2>
+<h2>🧑‍🤝‍🧑 Papers using deep-significance<a class="headerlink" href="#id17" title="Permalink to this headline">¶</a></h2>
+<p>In this last section of the readme, I would like to refer to works already using <code class="docutils literal notranslate"><span class="pre">deep-significance</span></code>. Open an issue or
+pull request if you would like to see your work added here!</p>
+<ul class="simple">
+<li><p><a class="reference external" href="https://robvanderg.github.io/doc/naacl2021.pdf">“From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding” (van der Groot et al., 2021)</a></p></li>
+<li><p><a class="reference external" href="https://arxiv.org/pdf/2109.04282.pdf">“Cartography Active Learning” (Zhang &amp; Plank, 2021)</a></p></li>
+</ul>
+</div>
+<div class="section" id="id18">
+<h2>📚 Bibliography<a class="headerlink" href="#id18" title="Permalink to this headline">¶</a></h2>
 <p>Del Barrio, Eustasio, Juan A. Cuesta-Albertos, and Carlos Matrán. “An optimal transportation approach for assessing almost stochastic order.” The Mathematics of the Uncertain. Springer, Cham, 2018. 33-44.</p>
 <p>Bonferroni, Carlo. “Teoria statistica delle classi e calcolo delle probabilita.” Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commericiali di Firenze 8 (1936): 3-62.</p>
 <p>Borji, Ali. “Negative results in computer vision: A perspective.” Image and Vision Computing 69 (2018): 1-8.</p>