Publications
(2015).
Learning to Detect Visual Grasp Affordance.
IEEE Transactions on Automation Science and Engineering. 13(2), 798-809.
(2016). Learning to Compose Neural Networks for Question Answering.
CoRR. abs/1601.01705,
(2016). Large Scale Visual Recognition Through Adaptation Using Joint Representation and Multiple Instance Learning.
J. Mach. Learn. Res.. 17, 4954–4984.
(2016). A Geometric Approach to Robotic Laundry Folding.
International Journal of Robotics Research. 31(2), 249-267.
(2012). Generalized Sparselet Models for Real-Time Multiclass Object Recognition.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 37, 1001-1012.
(2015). Gaussian Processes for Object Categorization.
International Journal of Computer Vision. 88(2), 169-188.
(2010). Fully Convolutional Networks for Semantic Segmentation.
IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(4), 640-651.
(2016). Fine-grained pose prediction, normalization, and recognition.
CoRR. abs/1511.07063,
(2015). End-to-end training of deep visuomotor policies.
Journal of Machine Learning Research. 17, 1–40.
(2016). Deep spatial autoencoders for visuomotor learning.
IEEE International Conference on Robotics and Automation (ICRA). 512-519.
(2016). Data-dependent Initializations of Convolutional Neural Networks.
CoRR. abs/1511.06856,
(2015). Constrained Structured Regression with Convolutional Neural Networks.
CoRR. abs/1511.07497,
(2015). Auxiliary Image Regularization for Deep CNNs with Noisy Labels.
CoRR. abs/1511.07069,
(2015). Adversarial Feature Learning.
CoRR. abs/1605.09782,
(2016). TSC-DL: Unsupervised trajectory segmentation of multi-modal surgical demonstrations with Deep Learning.
IEEE International Conference on Robotics and Automation (ICRA). 4150-4157.
(2016). Deep learning for tactile understanding from visual and haptic data.
IEEE International Conference on Robotics and Automation (ICRA). 536-543.
(2016). Cross-modal adaptation for RGB-D detection.
IEEE International Conference on Robotics and Automation (ICRA). 5032-5039.
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