Research Code

For most of our papers, the code we used in our experiments is freely available. Sometimes we also have datasets, trained models, etc. I have not posted all of that code here yet, as I am transitioning to hosting that code here. If you would like the code for one of our experiments, please email me and I will post if for you if we have it. Here are the code packages re-posted so far:
  • Go-Explore
  • Deep Visualization Toolbox (code , paper, video summary)
  • Huizinga J, Mouret JB, Clune J (2014) Evolving Neural Networks That Are Both Modular and Regular: HyperNeat Plus the Connection Cost Technique. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). 697-704 (code)
  • Clune J, Baptiste-Mouret J-B, Lipson H (2013) The evolutionary origins of modularity. Proceedings of the Royal Society B. 280: 20122863. (code, also here)(data)
  • Mengistu H, Huizinga J, Mouret JB, Clune J (2016) The evolutionary origins of hierarchy. PLoS Computational Biology. 12(6): e1004829. (data)
  • Norouzzadeh M, Nguyen A, Kosmala M, Swanson A, Palmer MS, Parker C, Clune J (2018) Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning. Proceedings of the National Academy of Sciences. 115:25. (code)
  • Tabak et al. (2018) Machine learning to classify animal species in camera trap images: Applications in ecology. Methods in Ecology and Evolution. 2018:00:1–6 (code)
  • Norouzzadeh M, Morris D, Beery S, Joshi N, Jojic N, Clune J (2019) A deep active learning system for species identification and counting in camera trap images. http://arxiv.org/abs/1910.09716 (code)
  • Nguyen A, Dosovitskiy A, Yosinski J, Brox T, Clune J (2016) Synthesizing the preferred inputs for neurons in neural networks via deep generator networks. Advances in Neural Information Processing Systems (NeurIPS). (code)
  • Nguyen A, Clune J, Bengio Y, Dosovitskiy A, Yosinski J (2016) Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space. Computer Vision and Pattern Recognition (CVPR). (code)
  • Nguyen A, Yosinski J, Clune J (2015) Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images. Computer Vision and Pattern Recognition (CVPR). (code)
  • Nguyen A, Yosinski J, Clune J (2016) Multifaceted Feature Visualization: Uncovering the different types of features learned by each neuron in deep neural networks. ICML Workshop on Visualization for Deep Learning. (code)
  • Nguyen A, Yosinski J, Clune J (2016) Understanding Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning. Evolutionary Computation Journal. (code)
  • Huizinga J, Clune J (2018) Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm. https://arxiv.org/abs/1807.03392 (code)
  • Huizinga J, Stanley K, Clune J (2018) The emergence of canalization and evolvability in an open-ended, interactive evolutionary system. Artificial Life. 24:3: 157-181. (code for CPPNX)