coarse-grained-forecasting-benchmark commited on
Commit
266116d
·
verified ·
1 Parent(s): 41dd7e0

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +9 -0
README.md CHANGED
@@ -55,6 +55,15 @@ python -m reproduce.table2 generate --system euler --method cascaded_si \
55
 
56
  The code names the systems `euler`, `sqg`, `waves`, `nlkg` and `passive_scalar`, and the methods `direct_si`, `cascaded_si` and `edm`; add `--S <depth>` for a depth-sweep model. `SHA256SUMS` lists the file checksums.
57
 
 
 
 
 
 
 
 
 
 
58
  ## License
59
 
60
  Creative Commons Attribution 4.0 International (CC BY 4.0).
 
55
 
56
  The code names the systems `euler`, `sqg`, `waves`, `nlkg` and `passive_scalar`, and the methods `direct_si`, `cascaded_si` and `edm`; add `--S <depth>` for a depth-sweep model. `SHA256SUMS` lists the file checksums.
57
 
58
+ ## Reproduction code
59
+
60
+ The anonymous reproduction code is available in the [`code/`](./tree/main/code) directory.
61
+
62
+ It includes the implementations of Direct SI, Cascaded SI, and EDM, together with the configurations and scripts used to reproduce the paper's benchmark results.
63
+
64
+ See [`code/README.md`](./blob/main/code/README.md) for installation and evaluation instructions.
65
+
66
+
67
  ## License
68
 
69
  Creative Commons Attribution 4.0 International (CC BY 4.0).