fixing refs

paper/paper.md

@@ -54,7 +54,7 @@ generated by a latent state, $z_t$, which evolve according to a transition
 $u_t$, to steer the latent state dynamics and influence the observations.
 
 For example, SSMs are often used in neuroscience to model the dynamics of 
-neural spike train recordings [@vyas:2020]. Here, $y_t$ is a vector of spike 
+neural spike train recordings [@vyas2020computation]. Here, $y_t$ is a vector of spike 
 counts from each of, say, 100 measured neurons. The activity of nearby neurons 
 is often correlated, and SSMs can capture that correlation through a lower 
 dimensional latent state, $z_t$. Finally, if we know that certain sensory inputs 
@@ -106,7 +106,7 @@ linear Gaussian SSMs.
 in machine learning research [@zhao2023revisiting; @lee2023switching; @chang2023low]. 
 More sophisticated, special purpose models on top of `Dynamax`, like the 
 Keypoint-MoSeq library for modeling postural dynamics
-of animals [@Weinreb:2024]. Finally, the `Dynamax` tutorials are used as reference 
+of animals [@weinreb2024keypoint]. Finally, the `Dynamax` tutorials are used as reference 
 examples in a major machine learning textbook [@murphy2023probabilistic]. 
 
 # Acknowledgements