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Alexei A. Efros | Yu Sun | Pieter Abbeel | Xiaolong Wang | Lerrel Pinto | Nicklas Hansen | P. Abbeel | Lerrel Pinto | Xiaolong Wang | Yu Sun | Nicklas Hansen
[1] Dacheng Tao,et al. Domain Generalization via Conditional Invariant Representations , 2018, AAAI.
[2] Pieter Abbeel,et al. Planning to Explore via Self-Supervised World Models , 2020, ICML.
[3] Yuval Tassa,et al. DeepMind Control Suite , 2018, ArXiv.
[4] R. Stephenson. A and V , 1962, The British journal of ophthalmology.
[5] Nikos Komodakis,et al. Unsupervised Representation Learning by Predicting Image Rotations , 2018, ICLR.
[6] Alexei A. Efros,et al. Colorful Image Colorization , 2016, ECCV.
[7] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[8] Sergey Levine,et al. Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control , 2018, ArXiv.
[9] Jakub W. Pachocki,et al. Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..
[10] S. Sastry,et al. Adaptive Control: Stability, Convergence and Robustness , 1989 .
[11] Geoffrey E. Hinton,et al. A Simple Framework for Contrastive Learning of Visual Representations , 2020, ICML.
[12] Kibok Lee,et al. A Simple Randomization Technique for Generalization in Deep Reinforcement Learning , 2019, ICLR 2020.
[13] Sergey Levine,et al. (CAD)$^2$RL: Real Single-Image Flight without a Single Real Image , 2016, Robotics: Science and Systems.
[14] Yuan Shi,et al. Geodesic flow kernel for unsupervised domain adaptation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Sergey Levine,et al. QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation , 2018, CoRL.
[16] Dacheng Tao,et al. Domain Generalization via Conditional Invariant Representation , 2018, ArXiv.
[17] Hongyuan Zha,et al. Single Episode Policy Transfer in Reinforcement Learning , 2019, ICLR.
[18] Alexei A. Efros,et al. Unsupervised Visual Representation Learning by Context Prediction , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[19] Stella X. Yu,et al. Unsupervised Feature Learning via Non-parametric Instance Discrimination , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[20] Alexei A. Efros,et al. Context Encoders: Feature Learning by Inpainting , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Joelle Pineau,et al. Improving Sample Efficiency in Model-Free Reinforcement Learning from Images , 2019, ArXiv.
[22] Tatsuya Harada,et al. Domain Generalization Using a Mixture of Multiple Latent Domains , 2019, AAAI.
[23] Kaiming He,et al. Momentum Contrast for Unsupervised Visual Representation Learning , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Benjamin Recht,et al. A systematic framework for natural perturbations from videos , 2019, ArXiv.
[25] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[26] Ali Razavi,et al. Data-Efficient Image Recognition with Contrastive Predictive Coding , 2019, ICML.
[27] B. Pasik-Duncan,et al. Adaptive Control , 1996, IEEE Control Systems.
[28] Tom Schaul,et al. Reinforcement Learning with Unsupervised Auxiliary Tasks , 2016, ICLR.
[29] Balaraman Ravindran,et al. EPOpt: Learning Robust Neural Network Policies Using Model Ensembles , 2016, ICLR.
[30] Alexei A. Efros,et al. Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[31] Sergey Levine,et al. Visual Reinforcement Learning with Imagined Goals , 2018, NeurIPS.
[32] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[33] Benjamin Recht,et al. Do Image Classifiers Generalize Across Time , 2019 .
[34] Pieter Abbeel,et al. CURL: Contrastive Unsupervised Representations for Reinforcement Learning , 2020, ICML.
[35] Paolo Favaro,et al. Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles , 2016, ECCV.
[36] Benjamin Recht,et al. Do ImageNet Classifiers Generalize to ImageNet? , 2019, ICML.
[37] Martin A. Riedmiller,et al. Deep auto-encoder neural networks in reinforcement learning , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).
[38] Pieter Abbeel,et al. Reinforcement Learning with Augmented Data , 2020, NeurIPS.
[39] Bolei Zhou,et al. Semantic photo manipulation with a generative image prior , 2019, ACM Trans. Graph..
[40] Alexei A. Efros,et al. Test-Time Training with Self-Supervision for Generalization under Distribution Shifts , 2019, ICML.
[41] Ilya Kostrikov,et al. Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels , 2020, ArXiv.
[42] Dawn Song,et al. Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty , 2019, NeurIPS.
[43] Dieter Fox,et al. BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators , 2019, Robotics: Science and Systems.
[44] Razvan Pascanu,et al. Progressive Neural Networks , 2016, ArXiv.
[45] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[46] Jürgen Schmidhuber,et al. Recurrent World Models Facilitate Policy Evolution , 2018, NeurIPS.
[47] Michael I. Jordan,et al. Unsupervised Domain Adaptation with Residual Transfer Networks , 2016, NIPS.
[48] Abhinav Gupta,et al. Robust Adversarial Reinforcement Learning , 2017, ICML.
[49] Alexei A. Efros,et al. Unsupervised Domain Adaptation through Self-Supervision , 2019, ArXiv.
[50] Abhinav Gupta,et al. Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[51] Andrew Zisserman,et al. Multi-task Self-Supervised Visual Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[52] Benjamin Recht,et al. Do CIFAR-10 Classifiers Generalize to CIFAR-10? , 2018, ArXiv.
[53] Allan Jabri,et al. Learning Correspondence From the Cycle-Consistency of Time , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[54] Marek Wydmuch,et al. ViZDoom Competitions: Playing Doom From Pixels , 2018, IEEE Transactions on Games.
[55] Mengjie Zhang,et al. Domain Generalization for Object Recognition with Multi-task Autoencoders , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[56] Wojciech Zaremba,et al. Domain randomization for transferring deep neural networks from simulation to the real world , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[57] Ali Farhadi,et al. Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[58] Matthias Bethge,et al. Generalisation in humans and deep neural networks , 2018, NeurIPS.
[59] Trevor Darrell,et al. Adversarial Discriminative Domain Adaptation , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[60] P. Cochat,et al. Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.
[61] François Laviolette,et al. Domain-Adversarial Training of Neural Networks , 2015, J. Mach. Learn. Res..
[62] Deva Ramanan,et al. Online Model Distillation for Efficient Video Inference , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[63] Thomas G. Dietterich,et al. Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations , 2018, 1807.01697.
[64] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[65] Alexei A. Efros,et al. Curiosity-Driven Exploration by Self-Supervised Prediction , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[66] Henry Zhu,et al. Soft Actor-Critic Algorithms and Applications , 2018, ArXiv.
[67] Sergey Levine,et al. Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[68] Sergey Levine,et al. Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[69] Eugenio Culurciello,et al. Continual Reinforcement Learning in 3D Non-stationary Environments , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[70] Dawn Xiaodong Song,et al. Assessing Generalization in Deep Reinforcement Learning , 2018, ArXiv.
[71] Gaurav S. Sukhatme,et al. Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning , 2020 .
[72] Michal Irani,et al. InGAN: Capturing and Retargeting the “DNA” of a Natural Image , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[73] Shai Bagon,et al. InGAN: Capturing and Remapping the "DNA" of a Natural Image , 2018 .
[74] Michal Irani,et al. "Zero-Shot" Super-Resolution Using Deep Internal Learning , 2017, CVPR.
[75] Marcin Andrychowicz,et al. Sim-to-Real Transfer of Robotic Control with Dynamics Randomization , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[76] Marcin Andrychowicz,et al. Asymmetric Actor Critic for Image-Based Robot Learning , 2017, Robotics: Science and Systems.
[77] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[78] Pieter Abbeel,et al. Learning Predictive Representations for Deformable Objects Using Contrastive Estimation , 2020, CoRL.
[79] Nitish Srivastava. Unsupervised Learning of Visual Representations using Videos , 2015 .