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Found 4 papers, 1 papers with code
Sequential training of GANs against GAN-classifiers reveals correlated "knowledge gaps" present among independently trained GAN instances
We iteratively train GAN-classifiers and train GANs that "fool" the classifiers (in an attempt to fill the knowledge gaps), and examine the effect on GAN training dynamics, output quality, and GAN-classifier generalization.
High Fidelity Video Prediction with Large Stochastic Recurrent Neural Networks
Predicting future video frames is extremely challenging, as there are many factors of variation that make up the dynamics of how frames change through time.
Learning 6-DOF Grasping Interaction via Deep Geometry-aware 3D Representations
Our contributions are fourfold: (1) To best of our knowledge, we are presenting for the first time a method to learn a 6-DOF grasping net from RGBD input; (2) We build a grasping dataset from demonstrations in virtual reality with rich sensory and interaction annotations.
A Two-Phase Approach Towards Identifying Argument Structure in Natural Language
We also propose two baselines and observe that the proposed approach outperforms baseline systems for the final task of Structure Prediction.
