Timestep distribution = Logit Normal and Loss weight function = Min_SNR_Gamma, Impact of new noise distribution on loss weight function ?

[Zokreb]

Hello community,

Maybe my question makes no sense, if this is the case, please say so, but i'd be happy if you could say why.

Since we have had access to stable diffusion fine-tuning, LoRas etc., we have seen improvement on loss weight function during training and the processing of noise with Min_SNR_Gamma and later Debiased Estimation.
This "math" have been developped when SD1.5 and later SDXL were king and those models were using uniform timestep distribution of noise.

With the arrival of SD3 and Flux models, we have had models that have been using Logit_Normal noise scheduling.
Does this have an impact on the loss weight function we use ? Are Min_SNR_Gamma or Debiased_Estimation still the "go to"* loss weight function ?
*When I say "go to", it's at least based on personal experience on SD1.5 and XL where I've always had my best results using either Min SNR or Debiased Estimation, i'm sure there can be some cases where the usual "math" (I do not know the appropriate word, was it MSE ?)

Thank you very much for your insights!