Upated readme

README.md

@@ -8,9 +8,6 @@ This Ising model dataset is an comprehensive open-source collection of typical a
 
 To further promote interdisciplinary physics applications with the ML community, our collection of Ising model datasets are curated from various ML papers/textbooks proposing Ising models applications. We organize the datasets based on dimensionality and geometery of Ising models.
 
-# License
-The dataset is licensed under OpenMDW-1.0. It is a permissive open model license. It allows anyone to freely use, modify, and redistribute the model materials — including model architectures, parameters, data, and documentation — for any purpose, including for commercial purposes, provided that the license text is included with any redistributed version. There are no restrictions on the use or licensing of any outputs, models, or results derived from the data.
-
 # Dataset References
 
 | **Directory Name** | **Paper** | **Reference** |
@@ -24,4 +21,7 @@ The dataset is licensed under OpenMDW-1.0. It is a permissive open model license
 | QMMC  | Quantum-Enhanced Markov Monte Carlo                                                          | [7](references.bib) | 
 | DRL   | Searching for spin glass ground states through deep reinforcement learning                   | [8](references.bib) | 
 | VAN   | Solving Statistical Mechanics Using Variational Autoregressive Networks                      | [9](references.bib) | 
-| VNA   | Variational Neural Annealing                                                                 | [10](references.bib) | 
+| VNA   | Variational Neural Annealing                                                                 | [10](references.bib) | 
+
+# License
+The dataset is licensed under OpenMDW-1.0. It is a permissive open model license. It allows anyone to freely use, modify, and redistribute the model materials — including model architectures, parameters, data, and documentation — for any purpose, including for commercial purposes, provided that the license text is included with any redistributed version. There are no restrictions on the use or licensing of any outputs, models, or results derived from the data.