diff --git a/_posts/2023-05-01-hitchhikers-momentum.md b/_posts/2023-05-01-hitchhikers-momentum.md
index 43c0c8c1..9de66480 100644
--- a/_posts/2023-05-01-hitchhikers-momentum.md
+++ b/_posts/2023-05-01-hitchhikers-momentum.md
@@ -265,7 +265,7 @@ difference between the current and the previous iterate $$(\xx_{t} - \xx_{t-1})$
 
 Despite its simplicity, gradient descent with momentum exhibits unexpectedly rich dynamics that we'll explore on this post. 
 
-### History and relatex work
+### History and related work
 
 The origins of momentum can be traced back to Frankel's method in the 1950s for solving linear system of equations.<d-cite key="frankel1950convergence"></d-cite> It was later generalized by Boris Polyak to non-quadratic objectives<d-cite key="polyak1964some"></d-cite>.
 While the quadratic case is by now well understood, the general strongly convex case has instead had some fascinating developments in the last years.
@@ -564,4 +564,4 @@ Plotting the asymptotic rates for all regions we can see that Polyak momentum (t
 
 ## Reproducibility
 
-All plots in this post were generated using the following Jupyer notebook: [[HTML]]({{'assets/html/2023-05-01-hitchhikers-momentum/hitchhikers-momentum.html' | relative_url}}) [[IPYNB]]({{'assets/html/2023-05-01-hitchhikers-momentum/hitchhikers-momentum.ipynb' | relative_url}})
\ No newline at end of file
+All plots in this post were generated using the following Jupyer notebook: [[HTML]]({{'assets/html/2023-05-01-hitchhikers-momentum/hitchhikers-momentum.html' | relative_url}}) [[IPYNB]]({{'assets/html/2023-05-01-hitchhikers-momentum/hitchhikers-momentum.ipynb' | relative_url}})