Merge pull request #7 from jbytecode/paper

minor fixes

Author: AlanPearl

paper/paper.bib

@@ -141,7 +141,7 @@ @INPROCEEDINGS{Li:2005
 @ARTICLE{Blank:2020,
     author={J. {Blank} and K. {Deb}},
     journal={IEEE Access},
-    title={pymoo: Multi-Objective Optimization in Python},
+    title={pymoo: Multi-Objective Optimization in {P}ython},
     year={2020},
     volume={8},
     number={},

paper/paper.md

@@ -127,8 +127,8 @@ model data, respectively.
 The analogous `compare_fourier_counts` method can provide additional loss 
 terms relating to differences in the empirical characteristic function (ECF; 
 @Cramer:1954). It is evaluated at a random sample of (20 by default) 
-fourier-space positions, $\vec{\tilde{x}}_k$, for both the "true" and "model" 
-fourier counts:
+Fourier-space positions, $\vec{\tilde{x}}_k$, for both the "true" and "model" 
+Fourier counts:
 
 $$ \tilde{N}_k = \sum\limits_i \exp(i \vec{\tilde{x}}_k \cdot \vec{x}_i). $$