From 5878966045654f45d913eda71501b2e95a8b8b29 Mon Sep 17 00:00:00 2001
From: franckma31 <49721198+franckma31@users.noreply.github.com>
Date: Tue, 13 Dec 2022 22:50:48 +0100
Subject: [PATCH 1/2] add comments on reference papers

---
 deel/lip/regularizers.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/deel/lip/regularizers.py b/deel/lip/regularizers.py
index 07a192dd..95907688 100644
--- a/deel/lip/regularizers.py
+++ b/deel/lip/regularizers.py
@@ -38,6 +38,10 @@ def __init__(self, dim, kernel_shape=None, stride=1, conv_transpose=False) -> No
         """
         Base class for Lorth regularization. Not meant to be used standalone.
 
+        Ref. Achour & al., Existence, Stability And Scalability Of Orthogonal
+        Convolutional Neural Networks (2022).
+        https://hal.archives-ouvertes.fr/hal-03315801
+
         Args:
             dim (int): the rank of the convolution, e.g. "2" for 2D convolution.
             kernel_shape: the shape of the kernel.
@@ -80,6 +84,7 @@ def _alphaNormSpectral(self):
         return alpha
 
     def _check_if_orthconv_exists(self):
+        """check the existence of Orthogonal convolution (for circular padding)"""
         R, C, M = self._get_kernel_shape()
         msg = "Impossible {} configuration for orthogonal convolution."
         if C * self.stride**self.dim >= M:  # RO case
@@ -128,6 +133,9 @@ def __init__(self, kernel_shape=None, stride=1, conv_transpose=False) -> None:
         Lorth computation for 2D convolutions. Although this class allows to compute
         the regularization term, it cannot be used as it is in a layer.
 
+        Ref. Wang & al., Orthogonal Convolutional Neural Networks (2020).
+        http://arxiv.org/abs/1911.12207
+
         Args:
             kernel_shape: the shape of the kernel.
             stride (int): stride used in the associated convolution

From c87fe44ac44eda3ebc472b77a40ddbae891439d0 Mon Sep 17 00:00:00 2001
From: Franck Mamalet <franck.mamalet@irt-systemx.fr>
Date: Mon, 2 Jan 2023 15:10:11 +0100
Subject: [PATCH 2/2] change link to jmlr paper

---
 deel/lip/regularizers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/deel/lip/regularizers.py b/deel/lip/regularizers.py
index 95907688..a72dc079 100644
--- a/deel/lip/regularizers.py
+++ b/deel/lip/regularizers.py
@@ -40,7 +40,7 @@ def __init__(self, dim, kernel_shape=None, stride=1, conv_transpose=False) -> No
 
         Ref. Achour & al., Existence, Stability And Scalability Of Orthogonal
         Convolutional Neural Networks (2022).
-        https://hal.archives-ouvertes.fr/hal-03315801
+        https://www.jmlr.org/papers/v23/22-0026.html
 
         Args:
             dim (int): the rank of the convolution, e.g. "2" for 2D convolution.