Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Active model-based segmentation has frequently been used in medical image processing with considerable success. Although the active model-based method was initially viewed as an op...
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...