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TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training"
Single/multi view image(s) to voxel reconstruction using a recurrent neural network
Source code for "Understanding Deep Image Representations by Inverting Them", CVPR 2015
Training, generation, and analysis code for Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics
The main features of hep-lbdl/adversarial-jets are: Computer Vision Applications, Physics Research.
Projects with overlapping indexed features include: callysto/curriculum-notebooks. carpedm20/simulated-unsupervised-tensorflow — TensorFlow implementation of "Learning from Simulated and Unsupervised Images through Adversarial Training". chrischoy/3d-r2n2 — Single/multi view image(s) to voxel reconstruction using a recurrent neural network. dkirkby/machinelearningstatistics. ernestyalumni/compphys. aravindhm/deep-goggle — Source code for "Understanding Deep Image Representations by Inverting Them", CVPR 2015.