update gadnr doc

pygod-team · Jan 30, 2024 · fd2a662 · fd2a662
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diff --git a/README.rst b/README.rst
@@ -189,7 +189,7 @@ OCGNN               2021   GNN          Yes          [#Wang2021One]_
 CoLA                2021   GNN+AE+SSL   Yes          [#Liu2021Anomaly]_
 GUIDE               2021   GNN+AE       Yes          [#Yuan2021Higher]_
 CONAD               2022   GNN+AE+SSL   Yes          [#Xu2022Contrastive]_
-GADNR               2023   GNN+AE       Yes          [#Roy2023Gadnr]_
+GADNR               2024   GNN+AE       Yes          [#Roy2024Gadnr]_
 ==================  =====  ===========  ===========  ========================================
 
 
@@ -259,4 +259,4 @@ Reference
 
 .. [#Xu2022Contrastive] Xu, Z., Huang, X., Zhao, Y., Dong, Y., and Li, J., 2022. Contrastive Attributed Network Anomaly Detection with Data Augmentation. In Proceedings of the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD).
 
-.. [#Roy2023Gadnr] Roy, A., Shu, J., Li, J., Yang, C., Elshocht, O., Smeets, J. and Li, P., 2023. GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM).
+.. [#Roy2024Gadnr] Roy, A., Shu, J., Li, J., Yang, C., Elshocht, O., Smeets, J. and Li, P., 2024. GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM).
diff --git a/docs/index.rst b/docs/index.rst
@@ -105,7 +105,7 @@ OCGNN               2021   GNN          Yes          :class:`pygod.detector.OCGN
 CoLA                2021   GNN+AE+SSL   Yes          :class:`pygod.detector.CoLA`
 GUIDE               2021   GNN+AE       Yes          :class:`pygod.detector.GUIDE`
 CONAD               2022   GNN+AE+SSL   Yes          :class:`pygod.detector.CONAD`
-GADNR               2023   GNN+AE       Yes          :class:`pygod.detector.GADNR`
+GADNR               2024   GNN+AE       Yes          :class:`pygod.detector.GADNR`
 ==================  =====  ===========  ===========  ==============================================
 
 

diff --git a/docs/zreferences.bib b/docs/zreferences.bib
@@ -173,7 +173,7 @@ @article{kipf2016variational
   year={2016}
 }
 
-@inproceedings{roy2023gadnr,
+@inproceedings{roy2024gadnr,
   title  = {GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction},
   author = {Roy, Amit and Shu, Juan and Li, Jia and Yang, Carl and Elshocht, Olivier and Smeets, Jeroen and Li, Pan},
   booktitle={Proceedings of the 17th ACM International Conference on Web Search and Data Mining},

diff --git a/pygod/detector/gadnr.py b/pygod/detector/gadnr.py
@@ -19,9 +19,15 @@
 
 class GADNR(DeepDetector):
     """
-    The GAD-NR model.
+    Graph Anomaly Detection via Neighborhood Reconstruction
+
+    GAD-NR is a new type of GAE based on neighborhood reconstruction
+    for graph anomaly detection. GAD-NR aims to reconstruct the entire
+    neighborhood (including local structure, self attributes, and
+    neighbors attributes) around a node based on the corresponding node
+    representation.
     
-    See :cite:`roy2023gadnr` for details.
+    See :cite:`roy2024gadnr` for details.
     
     Parameters
     ----------

diff --git a/pygod/nn/gadnr.py b/pygod/nn/gadnr.py
@@ -14,15 +14,15 @@
 
 class GADNRBase(nn.Module):
     """
-    GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction
+    Graph Anomaly Detection via Neighborhood Reconstruction
 
-    GAD-NR, is a new type of GAE based on neighborhood reconstruction
+    GAD-NR is a new type of GAE based on neighborhood reconstruction
     for graph anomaly detection. GAD-NR aims to reconstruct the entire
     neighborhood (including local structure, self attributes, and 
     neighbors attributes) around a node based on the corresponding node
     representation.
 
-    See :cite:`roy2023gadnr` for details.
+    See :cite:`roy2024gadnr` for details.
 
     Parameters
     ----------