58 citations · 164 across the 6 of their papers we have counts for
7 papers
FDLS: A Deep Learning Approach to Production Quality, Controllable, and Retargetable Facial Performances
Wan-Duo Kurt Ma, Muhammad Ghifary, J. P. Lewis +2
Visual effects commonly requires both the creation of realistic synthetic humans as well as retargeting actors' performances to humanoid characters such as aliens and monsters. Ach…
Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation
Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang +2
In this paper, we propose a novel unsupervised domain adaptation algorithm based on deep learning for visual object recognition. Specifically, we design a new model called Deep Rec…
Strongly-Typed Recurrent Neural Networks
David Balduzzi, Muhammad Ghifary
Recurrent neural networks are increasing popular models for sequential learning. Unfortunately, although the most effective RNN architectures are perhaps excessively complicated, e…
Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization
Muhammad Ghifary, David Balduzzi, W. Bastiaan Kleijn +1
This paper addresses classification tasks on a particular target domain in which labeled training data are only available from source domains different from (but related to) the ta…
Compatible Value Gradients for Reinforcement Learning of Continuous Deep Policies
David Balduzzi, Muhammad Ghifary
This paper proposes GProp, a deep reinforcement learning algorithm for continuous policies with compatible function approximation. The algorithm is based on two innovations. Firstl…
Domain Generalization for Object Recognition with Multi-task Autoencoders
Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang +1
The problem of domain generalization is to take knowledge acquired from a number of related domains where training data is available, and to then successfully apply it to previousl…