Update README.md

cavalab · Oct 29, 2021 · e5ded47 · e5ded47
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@@ -24,35 +24,35 @@ Methods currently benchmarked:
 - Age-Fitness Pareto Optimization (Schmidt and Lipson 2009) 
  [paper](https://dl.acm.org/doi/pdf/10.1145/1830483.1830584)
  , 
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/cavalab/ellyn)
 - Age-Fitness Pareto Optimization with Co-evolved Fitness Predictors (Schmidt and Lipson 2009) 
  [paper](https://dl.acm.org/doi/pdf/10.1145/1830483.1830584?casa_token=8fAFUrPlfuUAAAAA:u0QJvX-cC8rPtdZri-Jd4ZxcnRSIF_Fu2Vn5n-oXVNu_i71J6ZECx28ucLPOLQY628drsEbg4aFvTw)
  , 
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/cavalab/ellyn)
 - AIFeynman 2.0 (Udrescu et al. 2020)
  [paper](https://arxiv.org/abs/2006.10782)
  ,
  [code](https://github.com/SJ001/AI-Feynman)
 - Bayesian Symbolic Regression (Jin et al. 2020)
  [paper](https://arxiv.org/abs/1910.08892)
  ,
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/ying531/MCMC-SymReg)
 - Deep Symbolic Regression (Petersen et al. 2020)
  [paper](https://arxiv.org/pdf/1912.04871)
  , 
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/brendenpetersen/deep-symbolic-optimization)
 - Fast Function Extraction (McConaghy 2011)
  [paper](http://trent.st/content/2011-GPTP-FFX-paper.pdf)
  ,
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/natekupp/ffx)
 - Feature Engineering Automation Tool (La Cava et al. 2017)
  [paper](https://arxiv.org/abs/1807.00981)
  ,
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/lacava/feat)
 - epsilon-Lexicase Selection (La Cava et al. 2016)
  [paper](https://arxiv.org/abs/1905.13266)
  ,
- [code](https://github.com/EpistasisLab/ellyn)
+ [code](https://github.com/cavalab/ellyn)
 - GP-based Gene-pool Optimal Mixing Evolutionary Algorithm (Virgolin et al. 2017)
  [paper](https://dl.acm.org/doi/pdf/10.1145/3071178.3071287?casa_token=CHa8EK_ic5gAAAAA:mOAOCu6CL-jHobGWKD2wco4NbpCyS-XTY5thb1dPPsyUkTkLHzmLMF41MWMGWLyFv1G8n-VFaqmXSw)
  ,