Deep Independently Recurrent Neural Network (IndRNN)

Benchmark Model Rank Results
language-modelling-on-penn-treebank-characterDense IndRNN#7Bit per Character (BPC): 1.18
language-modelling-on-penn-treebank-wordDense IndRNN+dynamic eval#12Test perplexity: 50.97
language-modelling-on-penn-treebank-wordDense IndRNN#26Test perplexity: 56.37
sequential-image-classification-on-sequentialDense IndRNN#13Permuted Accuracy: 97.2%Unpermuted Accuracy: 99.48%
skeleton-based-action-recognition-on-ntu-rgbd-60Dense IndRNN#66Accuracy (CS): 86.70Accuracy (CV): 93.97