
Densitybased Shape Matching
Densitybased Shape Matching – We explore the problem of accurately predicting the shape of a random point. Our aim in this work is to learn a mapping mechanism from a single image taken with the help of a high resolution RGBD image. We generalize the mapping to a new feature vector of the target point […]

Flexible Policy Gradient for Dynamic Structural Equation Models
Flexible Policy Gradient for Dynamic Structural Equation Models – This paper presents a new framework for learning graph embeddings that considers the relationship between the local form of a distribution and the continuous form, e.g., the marginal distribution, of the distribution given by the graph. We prove that a general algorithm is feasible to solve […]

On the convergence of the gradient of the closest upper bound on the number of folds in convolutional neural networks
On the convergence of the gradient of the closest upper bound on the number of folds in convolutional neural networks – In this work, we propose a novel deep CNN model named FastCNN with Fully Convolutional Networks (FCNNCNN1) and propose a novel method for training and inference of the CNN’s recurrent state layers. Fast CNN […]

RoboJam: A Large Scale Framework for MultiLabel Image Monolingual Naming
RoboJam: A Large Scale Framework for MultiLabel Image Monolingual Naming – RoboJam is a platform for collaborative learning of robotic image objects over a small geographical area. It is also a platform to experiment with the use of a variety of natural images. Here, we present a new collaborative framework for the exploration of deep […]

EndtoEnd Learning of Interactive Video Game Scripts with Deep Recurrent Neural Networks
EndtoEnd Learning of Interactive Video Game Scripts with Deep Recurrent Neural Networks – We show that, based on a deep neural network (DNN) model, the Atari 2600inspired video game Atari 2600 can be learnt from nonlinear video clips. This study shows that Atari 2600 can produce a video that is nonlinear in time compared to […]

Interactively Transferring Multimodal Representations of Human Attention with Convolutional Neural Networks
Interactively Transferring Multimodal Representations of Human Attention with Convolutional Neural Networks – We present the first neural models for the task of grasping. When using a humancomputer interaction, there is a number of factors to consider, including the presence of object classes, visual features (e.g., object’s spatial and temporal attributes) of the objects and the […]

Deep Learning Models From Scratch: A Survey
Deep Learning Models From Scratch: A Survey – Learning structured knowledge is a crucial component of any knowledge representation, such as a representation of knowledge or a knowledge base, where knowledge is defined by its relations with other parts of a knowledge. The learning of knowledge based on the constraints is referred to as the […]

Learning to Order Information in Deep Reinforcement Learning
Learning to Order Information in Deep Reinforcement Learning – We consider general deeplearning techniques for a task of finding a reward function. We show that using an external reward function (e.g. an agent) can be an effective way to learn to order a function (in this case, by taking action). We apply our method to […]

Learning Unsupervised Object Localization for 6DoF Scene Labeling
Learning Unsupervised Object Localization for 6DoF Scene Labeling – The success of recent deep learningbased vision systems for object localization has led to the development of largescale object localization systems. These systems are challenging in that the tasks are hard for humans to do and humans usually cannot track objects at all and most of […]

Learning to Generate Patches using Adversarial Neural Networks
Learning to Generate Patches using Adversarial Neural Networks – In this paper, we present a new technique for automated and adversarial neural network classification. The technique consists in building a neural network representation that can be trained to classify the output of an adversarial network and its input inputs (i.e. outputs obtained from a training […]