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Author: t-kalinowski

R/layers-recurrent.R

@@ -239,7 +239,7 @@ layer_cudnn_gru <- function(object, units,
 #' @template roxlate-recurrent-layer
 #'
 #' @section References:
-#' - [Long short-term memory](https://www.bioinf.jku.at/publications/older/2604.pdf) (original 1997 paper)
+#' - [Long short-term memory](http://www.bioinf.jku.at/publications/older/2604.pdf) (original 1997 paper)
 #' - [Supervised sequence labeling with recurrent neural networks](https://www.cs.toronto.edu/~graves/preprint.pdf)
 #' - [A Theoretically Grounded Application of Dropout in Recurrent Neural Networks](https://arxiv.org/abs/1512.05287)
 #'
@@ -291,7 +291,7 @@ function(object,
 #' @inheritParams layer_dense
 #'
 #' @section References:
-#' - [Long short-term memory](https://www.bioinf.jku.at/publications/older/2604.pdf) (original 1997 paper)
+#' - [Long short-term memory](http://www.bioinf.jku.at/publications/older/2604.pdf) (original 1997 paper)
 #' - [Supervised sequence labeling with recurrent neural networks](https://www.cs.toronto.edu/~graves/preprint.pdf)
 #' - [A Theoretically Grounded Application of Dropout in Recurrent Neural Networks](https://arxiv.org/abs/1512.05287)
 #'

man/layer_cudnn_lstm.Rd

@@ -49,7 +49,7 @@ timestep is to be fed to the next timestep.
 [Cho et al., 2014](https://arxiv.org/abs/1406.1078).
 
 3. `layer_lstm()`, first proposed in
-[Hochreiter & Schmidhuber, 1997](https://www.bioinf.jku.at/publications/older/2604.pdf).
+[Hochreiter & Schmidhuber, 1997](http://www.bioinf.jku.at/publications/older/2604.pdf).
 
 Here is a simple example of a sequential model that processes sequences of integers,
 embeds each integer into a 64-dimensional vector, then processes the sequence of