split "paper" into "method" and "application"

Author: marvinschmitt

.github/workflows/bib2readme.py

@@ -9,7 +9,8 @@
 VALID_CATEGORIES = {
     "overview": "Overview Articles",
     "software": "Software",
-    "paper": "Research Articles",
+    "method": "Methodological Papers",
+    "application": "Application Papers",
     "uncategorized": "Uncategorized",
 }
 
@@ -193,7 +194,7 @@ def create_readme(entries_by_category: Dict[str, List[Entry]]) -> str:
     # Add Sections
     for category_key, category_value in VALID_CATEGORIES.items():
         if category_key in entries_by_category:
-            if category_key in ["overview", "paper", "uncategorized"]:
+            if category_key in ["overview", "method", "application", "uncategorized"]:
                 entries_by_category[category_key].sort(
                     key=lambda x: x.year if x.year.isdigit() else "0000", reverse=True
                 )

resources.bib

@@ -8,7 +8,7 @@ @article{dax2023neural
   publisher = {American Physical Society (APS)},
   author = {Dax,  Maximilian and Green,  Stephen R. and Gair,  Jonathan and P\"{u}rrer,  Michael and Wildberger,  Jonas and Macke,  Jakob H. and Buonanno,  Alessandra and Sch\"{o}lkopf,  Bernhard},
   year = {2023},
-  awesome-category = {paper},
+  awesome-category = {method},
   awesome-link-paper = {http://dx.doi.org/10.1103/PhysRevLett.130.171403},
 }
 
@@ -66,7 +66,7 @@ @InProceedings{radev2023jana
   volume = 	 {216},
   series = 	 {Proceedings of Machine Learning Research},
   publisher =    {PMLR},
-  awesome-category = {paper},
+  awesome-category = {method},
   awesome-link-paper = {https://proceedings.mlr.press/v216/radev23a}
 }
 
@@ -76,7 +76,7 @@ @misc{orozco2024aspire
 Year = {2024},
 Eprint = {arXiv:2405.05398},
 awesome-awesome-link-paper = {https://arxiv.org/abs/2405.05398},
-awesome-category = {paper}
+awesome-category = {method}
 }
 
 @misc{zammit-mangion2024neural,
@@ -121,7 +121,7 @@ @article{elsemueller2024sensitivity
   journal={Transactions on Machine Learning Research},
   issn={2835-8856},
   year={2024},
-  awesome-category = {paper},
+  awesome-category = {method},
   awesome-link-code = {https://github.com/bayesflow-org/SA-ABI},
   awesome-link-paper = {https://openreview.net/forum?id=Kxtpa9rvM0},
   awesome-tldr = {Efficient amortized sensitivity analyses with context variables}