📄 0-1 Loss 📄 Absolute Error 📄 Adversarial Loss 📄 Akaike Information Criterion 📄 Attention Alignment 📄 AUC-Borji 📄 AUC-Judd 📄 Bayesian Information Criterion 📄 BCE with Logits 📄 Bhattacharya Distance 📄 Binary Cross Entropy 📄 BLEU 📄 BYOL Loss 📄 BYOL 📄 Chebyshev Distance 📄 Chi Squared Distance 📄 Confusion Matrix 📄 Contrastive Loss 📄 Cosine Distance 📄 Cosine Learning Rate Decay 📄 Cosine Similarity 📄 Cross Entropy 📄 Cross Validation 📄 CTC 📄 Cycle Consistency Loss 📄 Dice Score 📄 Distance Measures 📄 Distillation Loss 📄 Earth Mover’s Distance (EMD) 📄 ELBO loss 📄 Emperical Risk 📄 Euclidean Distance 📄 Focal Loss 📄 GE2E 📄 Hamming Distance 📄 Hausdorff Distance 📄 Haversine Distance 📄 Hinge Loss 📄 Huber 📄 Identity Loss 📄 inter-sentence coherence loss 📄 Intra cluster variance 📄 ITM Loss 📄 Jaccard Distance 📄 Jensen Shannon Divergence Consistency Loss 📄 KL Divergence 📄 Least squares loss 📄 Log likelihood criterion 📄 Log Likelihood Loss 📄 LogCosh 📄 MAE 📄 Mallows Cp Statistic 📄 Manhattan Distance 📄 MAPE 📄 Margin Ranking 📄 Max Margin Loss 📄 Minkowski Distance 📄 MSE 📄 MSLE 📄 Negative Log Likelihood 📄 PatchGAN 📄 Perplexity 📄 Poisson Loss 📄 Precision Recall Curve 📄 Precision 📄 Quadratic Loss 📄 Quantile loss 📄 RAHP 📄 Recall 📄 Recipe for constructing loss functions 📄 Reconstruction loss 📄 ROC Curve 📄 SDR 📄 Sensitivity 📄 Shuffled-AUC 📄 Sørensen-Dice Index 📄 Sparse Dictionary Learning Loss 📄 Specificity 📄 Squared Error 📄 Squared Hinge 📄 SSR 📄 Triplet Loss