# Losses: Batch Inverse Variance (BIV)

class `losses.``BIVLoss`(epsilon=1e-05)
  Description:
    Batch Inverse variance loss is defined as:
  \[\mathcal{L}_{\mathrm{batch}}(D_i, \theta) = \left( \sum_{k=0}^K \dfrac{1}{\sigma_k^2 + \epsilon} \right)^{-1} \sum_{k=0}^K \dfrac{\mathcal{L}\left(f(x_k, \theta),\overline{y}_k\right)}{\sigma_k^2 + \epsilon} \label{eq:IVweighted_loss}\]
  `forward`(y_pred, y, lbl_var)
    Description:
      Compute the forward pass for BIV loss function.