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[1] Maximilian Karl,et al. Learning to Fly via Deep Model-Based Reinforcement Learning , 2020, ArXiv.
[2] Yannick Hold-Geoffroy,et al. Neural Reflectance Fields for Appearance Acquisition , 2020, ArXiv.
[3] Stefan Leutenegger,et al. CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[4] John J. Leonard,et al. Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age , 2016, IEEE Transactions on Robotics.
[5] Sergey Levine,et al. Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models , 2018, NeurIPS.
[6] Andrew J. Davison,et al. DeepFactors: Real-Time Probabilistic Dense Monocular SLAM , 2020, IEEE Robotics and Automation Letters.
[7] Yoshua Bengio,et al. Large-Scale Learning of Embeddings with Reconstruction Sampling , 2011, ICML.
[8] Ingmar Posner,et al. GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations , 2019, ICLR.
[9] Koray Kavukcuoglu,et al. Neural scene representation and rendering , 2018, Science.
[10] Ole Winther,et al. Sequential Neural Models with Stochastic Layers , 2016, NIPS.
[11] Fabio Viola,et al. Generative Temporal Models with Spatial Memory for Partially Observed Environments , 2018, ICML.
[12] Aaron van den Oord,et al. Shaping Belief States with Generative Environment Models for RL , 2019, NeurIPS.
[13] Jürgen Schmidhuber,et al. Recurrent World Models Facilitate Policy Evolution , 2018, NeurIPS.
[14] Mohammad Norouzi,et al. Dream to Control: Learning Behaviors by Latent Imagination , 2019, ICLR.
[15] Xiaoyue Jiang,et al. Robust Linear-Complexity Approach to Full SLAM Problems: Stochastic Variational Bayes Inference , 2019, 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall).
[16] Maximilian Karl,et al. Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data , 2016, ICLR.
[17] Stefan Leutenegger,et al. Towards the Probabilistic Fusion of Learned Priors into Standard Pipelines for 3D Reconstruction , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).
[18] Juan D. Tardós,et al. ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras , 2016, IEEE Transactions on Robotics.
[19] Honglak Lee,et al. Control of Memory, Active Perception, and Action in Minecraft , 2016, ICML.
[20] Ruslan Salakhutdinov,et al. Neural Map: Structured Memory for Deep Reinforcement Learning , 2017, ICLR.
[21] Shaojie Shen,et al. VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator , 2017, IEEE Transactions on Robotics.
[22] Shaojie Shen,et al. A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors , 2019, ArXiv.
[23] Gordon Wetzstein,et al. Implicit Neural Representations with Periodic Activation Functions , 2020, NeurIPS.
[24] Ruslan Salakhutdinov,et al. Active Neural Localization , 2018, ICLR.
[25] Daan Wierstra,et al. Recurrent Environment Simulators , 2017, ICLR.
[26] Daniel Cremers,et al. Direct Sparse Odometry , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[28] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[29] Sertac Karaman,et al. The Blackbird UAV dataset , 2020, Int. J. Robotics Res..
[30] Julien Cornebise,et al. Weight Uncertainty in Neural Networks , 2015, ArXiv.
[31] Yoshua Bengio,et al. A Recurrent Latent Variable Model for Sequential Data , 2015, NIPS.
[32] Ruben Villegas,et al. Learning Latent Dynamics for Planning from Pixels , 2018, ICML.
[33] HirschmullerHeiko. Stereo Processing by Semiglobal Matching and Mutual Information , 2008 .
[34] Ganesh Iyer,et al. ∇SLAM: Dense SLAM meets Automatic Differentiation , 2019, 2020 IEEE International Conference on Robotics and Automation (ICRA).
[35] Xiaoyue Jiang,et al. Linear-complexity stochastic variational Bayes inference for SLAM , 2017, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).
[36] Michael I. Jordan,et al. An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.
[37] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[38] Jonathan T. Barron,et al. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis , 2020, ECCV.
[39] Justin Bayer,et al. Approximate Bayesian inference in spatial environments , 2018, Robotics: Science and Systems.
[40] Sebastian Thrun,et al. FastSLAM: a factored solution to the simultaneous localization and mapping problem , 2002, AAAI/IAAI.
[41] Kevin P. Murphy,et al. Bayesian Map Learning in Dynamic Environments , 1999, NIPS.
[42] Andrew J. Davison,et al. DTAM: Dense tracking and mapping in real-time , 2011, 2011 International Conference on Computer Vision.
[43] Davide Scaramuzza,et al. VIMO: Simultaneous Visual Inertial Model-Based Odometry and Force Estimation , 2019, IEEE Robotics and Automation Letters.
[44] Fabio Tozeto Ramos,et al. Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping , 2017, CoRL.
[45] Ping Tan,et al. BA-Net: Dense Bundle Adjustment Network , 2018, ICLR.
[46] Thomas Brox,et al. DeepTAM: Deep Tracking and Mapping , 2018, ECCV.
[47] Wulfram Gerstner,et al. Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation , 2018, ICML.
[48] Felix Berkenkamp,et al. Structured Variational Inference in Partially Observable UnstableGaussian Process State Space Models , 2020, L4DC.