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ORCIDFabio Ramos 0001
Fabio T. Ramos 0001 – Fabio Tozeto Ramos
Person information
- affiliation: University of Sydney, School of Computer Science, Australia
- affiliation: NVIDIA, Seattle, WA, USA
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2020 – today
- 2022
[j36]Fabio Muratore, Fabio Ramos, Greg Turk, Wenhao Yu, Michael Gienger, Jan Peters:
Robot Learning From Randomized Simulations: A Review. Frontiers Robotics AI 9: 799893 (2022)- [j35]Fahira Afzal Maken
, Fabio Ramos, Lionel Ott:
Bayesian iterative closest point for mobile robot localization. Int. J. Robotics Res. 41(9-10): 851-874 (2022) - [j34]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Stein ICP for Uncertainty Estimation in Point Cloud Matching. IEEE Robotics Autom. Lett. 7(2): 1063-1070 (2022) - [j33]Tin Lai, Fabio Ramos:
Adaptively Exploits Local Structure With Generalised Multi-Trees Motion Planning. IEEE Robotics Autom. Lett. 7(2): 1111-1117 (2022) - [j32]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Stein Particle Filter for Nonlinear, Non-Gaussian State Estimation. IEEE Robotics Autom. Lett. 7(2): 5421-5428 (2022) - [j31]Rika Antonova, Jingyun Yang, Priya Sundaresan, Dieter Fox, Fabio Ramos, Jeannette Bohg:
A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation. IEEE Robotics Autom. Lett. 7(3): 5819-5826 (2022) - [c161]Krishna Murthy Jatavallabhula, Miles Macklin, Dieter Fox, Animesh Garg, Fabio Ramos:
Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming. CoRL 2022: 1563-1574 - [c160]Jie Xu, Viktor Makoviychuk, Yashraj S. Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin:
Accelerated Policy Learning with Parallel Differentiable Simulation. ICLR 2022 - [c159]Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos:
Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks. ICML 2022: 27060-27074 - [c158]Eric Heiden, Christopher E. Denniston, David Millard, Fabio Ramos, Gaurav S. Sukhatme:
Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation. ICRA 2022: 3638-3645 - [c157]Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty. ICRA 2022: 5539-5545 - [c156]Julia Tan, Ransalu Senanayake, Fabio Ramos:
Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills. IROS 2022: 7052-7059 - [c155]Tin Lai, Fabio Ramos:
LTR*: Rapid Replanning in Executing Consecutive Tasks with Lazy Experience Graph. IROS 2022: 8784-8790 - [c154]Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Adaptive Model Predictive Control by Learning Classifiers. L4DC 2022: 480-491 - [c153]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Diffeomorphic Transforms for Generalised Imitation Learning. L4DC 2022: 508-519 - [c152]Houston Warren, Rafael Oliveira, Fabio T. Ramos:
Generalized Bayesian quadrature with spectral kernels. UAI 2022: 2085-2095 - [i75]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Stein Particle Filter for Nonlinear, Non-Gaussian State Estimation. CoRR abs/2202.04213 (2022) - [i74]Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Bayesian Optimisation for Robust Model Predictive Control under Model Parameter Uncertainty. CoRR abs/2203.00551 (2022) - [i73]Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos:
L4KDE: Learning for KinoDynamic Tree Expansion. CoRR abs/2203.00975 (2022) - [i72]Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Adaptive Model Predictive Control by Learning Classifiers. CoRR abs/2203.06783 (2022) - [i71]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting. CoRR abs/2203.10263 (2022) - [i70]Jie Xu, Viktor Makoviychuk, Yashraj S. Narang, Fabio T. Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin:
Accelerated Policy Learning with Parallel Differentiable Simulation. CoRR abs/2204.07137 (2022) - [i69]Julia Tan, Ransalu Senanayake, Fabio Ramos:
Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills. CoRR abs/2207.00978 (2022) - [i68]Rafael Oliveira, Louis C. Tiao, Fabio Ramos:
Batch Bayesian optimisation via density-ratio estimation with guarantees. CoRR abs/2209.10715 (2022) - 2021
- [j30]Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Heteroscedastic Bayesian Optimisation for Stochastic Model Predictive Control. IEEE Robotics Autom. Lett. 6(1): 56-63 (2021) - [c151]Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos:
Parallelised Diffeomorphic Sampling-based Motion Planning. CoRL 2021: 81-90 - [c150]Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan D. Ratliff, Dieter Fox, Fabio Ramos, Byron Boots:
STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation. CoRL 2021: 750-759 - [c149]Louis C. Tiao, Aaron Klein, Matthias W. Seeger, Edwin V. Bonilla, Cédric Archambeau, Fabio Ramos:
BORE: Bayesian Optimization by Density-Ratio Estimation. ICML 2021: 10289-10300 - [c148]Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu:
Fast Uncertainty Quantification for Deep Object Pose Estimation. ICRA 2021: 5200-5207 - [c147]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements. ICRA 2021: 8459-8464 - [c146]Tin Lai, Fabio Ramos:
PlannerFlows: Learning Motion Samplers with Normalising Flows. IROS 2021: 2542-2548 - [c145]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Trajectory Generation in New Environments from Past Experiences. IROS 2021: 7911-7918 - [c144]Weiming Zhi, Lionel Ott, Fabio Ramos:
Probabilistic Trajectory Prediction with Structural Constraints. IROS 2021: 9849-9856 - [c143]Lucas Barcelos, Alexander Lambert, Rafael Oliveira, Paulo Borges, Byron Boots, Fabio Ramos:
Dual Online Stein Variational Inference for Control and Dynamics. Robotics: Science and Systems 2021 - [c142]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting. Robotics: Science and Systems 2021 - [c141]Rafael Oliveira, Lionel Ott, Fabio Ramos:
No-regret approximate inference via Bayesian optimisation. UAI 2021: 2082-2092 - [i67]Louis C. Tiao, Aaron Klein, Matthias W. Seeger, Edwin V. Bonilla, Cédric Archambeau, Fabio Ramos:
BORE: Bayesian Optimization by Density-Ratio Estimation. CoRR abs/2102.09009 (2021) - [i66]Lucas Barcelos, Alexander Lambert, Rafael Oliveira, Paulo Borges, Byron Boots, Fabio Ramos:
Dual Online Stein Variational Inference for Control and Dynamics. CoRR abs/2103.12890 (2021) - [i65]Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan D. Ratliff, Dieter Fox, Fabio Ramos, Byron Boots:
Fast Joint Space Model-Predictive Control for Reactive Manipulation. CoRR abs/2104.13542 (2021) - [i64]Eric Heiden, Miles Macklin, Yashraj S. Narang, Dieter Fox, Animesh Garg, Fabio Ramos:
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting. CoRR abs/2105.12244 (2021) - [i63]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Stein ICP for Uncertainty Estimation in Point Cloud Matching. CoRR abs/2106.03287 (2021) - [i62]Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos:
Learning ODEs via Diffeomorphisms for Fast and Robust Integration. CoRR abs/2107.01650 (2021) - [i61]Weiming Zhi, Lionel Ott, Fabio Ramos:
Probabilistic Trajectory Prediction with Structural Constraints. CoRR abs/2107.04193 (2021) - [i60]Rika Antonova, Fabio Ramos, Rafael Possas, Dieter Fox:
BayesSimIG: Scalable Parameter Inference for Adaptive Domain Randomization with IsaacGym. CoRR abs/2107.04527 (2021) - [i59]Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos:
Parallelised Diffeomorphic Sampling-based Motion Planning. CoRR abs/2108.11775 (2021) - [i58]Eric Heiden, Christopher E. Denniston, David Millard, Fabio Ramos, Gaurav S. Sukhatme:
Probabilistic Inference of Simulation Parameters via Parallel Differentiable Simulation. CoRR abs/2109.08815 (2021) - [i57]Tin Lai, Fabio Ramos:
Rapid Replanning in Consecutive Pick-and-Place Tasks with Lazy Experience Graph. CoRR abs/2109.10209 (2021) - [i56]Fabio Muratore, Fabio Ramos, Greg Turk, Wenhao Yu, Michael Gienger, Jan Peters:
Robot Learning from Randomized Simulations: A Review. CoRR abs/2111.00956 (2021) - [i55]Rika Antonova, Jingyun Yang, Priya Sundaresan, Dieter Fox, Fabio Ramos, Jeannette Bohg:
A Bayesian Treatment of Real-to-Sim for Deformable Object Manipulation. CoRR abs/2112.05068 (2021) - 2020
- [j29]Tin Lai, Philippe Morere, Fabio Ramos, Gilad Francis:
Bayesian Local Sampling-Based Planning. IEEE Robotics Autom. Lett. 5(2): 1954-1961 (2020) - [c140]Carolyn Matl, Yashraj S. Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos:
STReSSD: Sim-To-Real from Sound for Stochastic Dynamics. CoRL 2020: 935-958 - [c139]Alexander Lambert, Fabio Ramos, Byron Boots, Dieter Fox, Adam Fishman:
Stein Variational Model Predictive Control. CoRL 2020: 1278-1297 - [c138]Bhairav Mehta, Ankur Handa, Dieter Fox, Fabio Ramos:
A User's Guide to Calibrating Robotic Simulators. CoRL 2020: 1326-1340 - [c137]Carolyn Matl, Yashraj S. Narang, Ruzena Bajcsy, Fabio Ramos, Dieter Fox:
Inferring the Material Properties of Granular Media for Robotic Tasks. ICRA 2020: 2770-2777 - [c136]Ajay Mandlekar, Fabio Ramos, Byron Boots, Silvio Savarese, Li Fei-Fei, Animesh Garg, Dieter Fox:
IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data. ICRA 2020: 4414-4420 - [c135]Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan D. Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox:
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning. ICRA 2020: 7505-7512 - [c134]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Estimating Motion Uncertainty with Bayesian ICP. ICRA 2020: 8602-8608 - [c133]Lucas Barcelos, Rafael Oliveira, Rafael Possas, Lionel Ott, Fabio Ramos:
DISCO: Double Likelihood-free Inference Stochastic Control. ICRA 2020: 10969-10975 - [c132]Rafael Possas, Lucas Barcelos, Rafael Oliveira, Dieter Fox, Fabio Ramos:
Online BayesSim for Combined Simulator Parameter Inference and Policy Improvement. IROS 2020: 5445-5452 - [c131]Muhammad Asif Rana, Anqi Li, Dieter Fox, Byron Boots, Fabio Ramos, Nathan D. Ratliff:
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems. L4DC 2020: 630-639 - [c130]Anthony Tompkins, Rafael Oliveira, Fabio T. Ramos:
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning. NeurIPS 2020 - [c129]Harrison Nguyen, Simon Luo, Fabio Ramos:
Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training. PAKDD (2) 2020: 409-421 - [c128]Anthony Tompkins, Ransalu Senanayake, Fabio Ramos:
Online Domain Adaptation for Occupancy Mapping. Robotics: Science and Systems 2020 - [c127]Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos:
Active Learning of Conditional Mean Embeddings via Bayesian Optimisation. UAI 2020: 1119-1128 - [e2]Jens Kober, Fabio Ramos, Claire J. Tomlin:
4th Conference on Robot Learning, CoRL 2020, 16-18 November 2020, Virtual Event / Cambridge, MA, USA. Proceedings of Machine Learning Research 155, PMLR 2020 [contents] - [i54]Philippe Morere, Gilad Francis, Tom Blau, Fabio Ramos:
Reinforcement Learning with Probabilistically Complete Exploration. CoRR abs/2001.06940 (2020) - [i53]Lucas Barcelos, Rafael Oliveira, Rafael Possas, Lionel Ott, Fabio Ramos:
DISCO: Double Likelihood-free Inference Stochastic Control. CoRR abs/2002.07379 (2020) - [i52]Carolyn Matl, Yashraj S. Narang, Ruzena Bajcsy, Fabio Ramos, Dieter Fox:
Inferring the Material Properties of Granular Media for Robotic Tasks. CoRR abs/2003.08032 (2020) - [i51]Philippe Morere, Fabio Ramos:
Intrinsic Exploration as Multi-Objective RL. CoRR abs/2004.02380 (2020) - [i50]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Estimating Motion Uncertainty with Bayesian ICP. CoRR abs/2004.07973 (2020) - [i49]Michelle A. Lee, Carlos Florensa, Jonathan Tremblay, Nathan D. Ratliff, Animesh Garg, Fabio Ramos, Dieter Fox:
Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learning. CoRR abs/2005.10872 (2020) - [i48]Muhammad Asif Rana, Anqi Li, Dieter Fox, Byron Boots, Fabio Ramos, Nathan D. Ratliff:
Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems. CoRR abs/2005.13143 (2020) - [i47]Anthony Tompkins, Ransalu Senanayake, Fabio Ramos:
Online Domain Adaptation for Occupancy Mapping. CoRR abs/2007.00164 (2020) - [i46]Rel Guzman Apaza, Rafael Oliveira, Fabio Ramos:
Heteroscedastic Bayesian Optimisation for Stochastic Model Predictive Control. CoRR abs/2010.00202 (2020) - [i45]Anthony Tompkins, Rafael Oliveira, Fabio Ramos:
Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning. CoRR abs/2010.04315 (2020) - [i44]Sebastian Haan, Fabio Ramos, Dietmar Müller:
Multi-Objective Bayesian Optimisation and Joint Inversion for Active Sensor Fusion. CoRR abs/2010.05386 (2020) - [i43]Tin Lai, Fabio Ramos:
Learning to Plan Optimally with Flow-based Motion Planner. CoRR abs/2010.11323 (2020) - [i42]Carolyn Matl, Yashraj S. Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos:
STReSSD: Sim-To-Real from Sound for Stochastic Dynamics. CoRR abs/2011.03136 (2020) - [i41]Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos:
Anticipatory Navigation in Crowds by Probabilistic Prediction of Pedestrian Future Movements. CoRR abs/2011.06235 (2020) - [i40]Alexander Lambert, Adam Fishman, Dieter Fox, Byron Boots, Fabio Ramos:
Stein Variational Model Predictive Control. CoRR abs/2011.07641 (2020) - [i39]Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu:
Fast Uncertainty Quantification for Deep Object Pose Estimation. CoRR abs/2011.07748 (2020) - [i38]Bhairav Mehta, Ankur Handa, Dieter Fox, Fabio Ramos:
A User's Guide to Calibrating Robotics Simulators. CoRR abs/2011.08985 (2020)
2010 – 2019
- 2019
- [j28]Kelen Cristiane Teixeira Vivaldini, Thiago H. Martinelli, Vitor Campanholo Guizilini, Jefferson R. Souza, Matheus Della Croce Oliveira, Fabio T. Ramos, Denis F. Wolf:
UAV route planning for active disease classification. Auton. Robots 43(5): 1137-1153 (2019) - [j27]Gilad Francis, Lionel Ott, Román Marchant, Fabio Ramos:
Occupancy map building through Bayesian exploration. Int. J. Robotics Res. 38(7) (2019) - [j26]Vitor Guizilini, Fabio Ramos:
Variational Hilbert regression for terrain modeling and trajectory optimization. Int. J. Robotics Res. 38(12-13) (2019) - [j25]Amir Dezfouli, Kristi Griffiths, Fabio Ramos, Peter Dayan, Bernard W. Balleine:
Models that learn how humans learn: The case of decision-making and its disorders. PLoS Comput. Biol. 15(6) (2019) - [j24]Philippe Morere, Lionel Ott, Fabio Ramos:
Learning to Plan Hierarchically From Curriculum. IEEE Robotics Autom. Lett. 4(3): 2815-2822 (2019) - [j23]Weiming Zhi, Ransalu Senanayake, Lionel Ott, Fabio Ramos:
Spatiotemporal Learning of Directional Uncertainty in Urban Environments With Kernel Recurrent Mixture Density Networks. IEEE Robotics Autom. Lett. 4(4): 4306-4313 (2019) - [c126]Rafael Oliveira, Lionel Ott, Fabio Ramos:
Bayesian optimisation under uncertain inputs. AISTATS 2019: 1177-1184 - [c125]Anthony Tompkins, Ransalu Senanayake, Philippe Morere, Fabio Ramos:
Black Box Quantiles for Kernel Learning. AISTATS 2019: 1427-1437 - [c124]Kelvin Hsu, Fabio Ramos:
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference. AISTATS 2019: 2631-2640 - [c123]Weiming Zhi, Lionel Ott, Fabio Ramos:
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction. CoRL 2019: 1405-1414 - [c122]Alexandre J. Oliveira, Gleice A. de Assis, Elaine R. Faria, Jefferson R. Souza, Kelen Cristiane Teixeira Vivaldini, Vitor Guizilini, Fabio Ramos, Caio César Teodoro Mendes, Denis F. Wolf:
Analysis of nematodes in coffee crops at different altitudes using aerial images. EUSIPCO 2019: 1-5 - [c121]Kelvin Hsu, Fabio Ramos:
Bayesian Deconditional Kernel Mean Embeddings. ICML 2019: 2830-2838 - [c120]Gilad Francis, Lionel Ott, Fabio Ramos:
Fast Stochastic Functional Path Planning in Occupancy Maps. ICRA 2019: 929-935 - [c119]Vitor Guizilini, Ransalu Senanayake, Fabio Ramos:
Dynamic Hilbert Maps: Real-Time Occupancy Predictions in Changing Environments. ICRA 2019: 4091-4097 - [c118]Weiming Zhi, Lionel Ott, Ransalu Senanayake, Fabio Ramos:
Continuous Occupancy Map Fusion with Fast Bayesian Hilbert Maps. ICRA 2019: 4111-4117 - [c117]Tin Lai, Fabio Ramos, Gilad Francis:
Balancing Global Exploration and Local-connectivity Exploitation with Rapidly-exploring Random disjointed-Trees. ICRA 2019: 5537-5543 - [c116]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Speeding Up Iterative Closest Point Using Stochastic Gradient Descent. ICRA 2019: 6395-6401 - [c115]Fabio Ramos, Rafael Possas, Dieter Fox:
BayesSim: Adaptive Domain Randomization Via Probabilistic Inference for Robotics Simulators. Robotics: Science and Systems 2019 - [c114]Anthony Tompkins, Fabio Ramos:
Periodic Kernel Approximation by Index Set Fourier Series Features. UAI 2019: 486-496 - [i37]Rafael Oliveira, Lionel Ott, Fabio Ramos:
Bayesian optimisation under uncertain inputs. CoRR abs/1902.07908 (2019) - [i36]Kelvin Hsu, Fabio Ramos:
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference. CoRR abs/1903.00863 (2019) - [i35]Kelvin Hsu, Fabio Ramos:
Bayesian Deconditional Kernel Mean Embeddings. CoRR abs/1906.00199 (2019) - [i34]Fabio Ramos, Rafael Carvalhaes Possas, Dieter Fox:
BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators. CoRR abs/1906.01728 (2019) - [i33]Philippe Morere, Lionel Ott, Fabio Ramos:
Learning to Plan Hierarchically from Curriculum. CoRR abs/1906.07371 (2019) - [i32]Weiming Zhi, Lionel Ott, Fabio Ramos:
Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction. CoRR abs/1907.05127 (2019) - [i31]Fahira Afzal Maken, Fabio Ramos, Lionel Ott:
Speeding Up Iterative Closest Point Using Stochastic Gradient Descent. CoRR abs/1907.09133 (2019) - [i30]Tin Lai, Weiming Zhi, Fabio Ramos:
Occ-Traj120: Occupancy Maps with Associated Trajectories. CoRR abs/1909.02333 (2019) - [i29]Tin Lai, Philippe Morere, Fabio Ramos, Gilad Francis:
Local Sampling-based Planning with Sequential Bayesian Updates. CoRR abs/1909.03452 (2019) - [i28]Weiming Zhi, Tin Lai, Lionel Ott, Gilad Francis, Fabio Ramos:
OCTNet: Trajectory Generation in New Environments from Past Experiences. CoRR abs/1909.11337 (2019) - [i27]Ajay Mandlekar, Fabio Ramos, Byron Boots, Li Fei-Fei, Animesh Garg, Dieter Fox:
IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Data. CoRR abs/1911.05321 (2019) - [i26]Tom Blau, Lionel Ott, Fabio Ramos:
Bayesian Curiosity for Efficient Exploration in Reinforcement Learning. CoRR abs/1911.08701 (2019) - [i25]Vitor Guizilini, Ransalu Senanayake, Fabio Ramos:
Dynamic Hilbert Maps: Real-Time Occupancy Predictions in Changing Environment. CoRR abs/1912.02149 (2019) - [i24]Harrison Nguyen, Simon Luo, Fabio Ramos:
Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training. CoRR abs/1912.04391 (2019) - 2018
- [j22]Vitor Guizilini, Fabio Ramos:
Towards real-time 3D continuous occupancy mapping using Hilbert maps. Int. J. Robotics Res. 37(6): 566-584 (2018) - [j21]Vitor Guizilini, Fabio Ramos:
Learning to reconstruct 3D structures for occupancy mapping from depth and color information. Int. J. Robotics Res. 37(13-14) (2018) - [j20]Alberto Y. Hata, Fabio T. Ramos, Denis F. Wolf:
Monte Carlo Localization on Gaussian Process Occupancy Maps for Urban Environments. IEEE Trans. Intell. Transp. Syst. 19(9): 2893-2902 (2018) - [c113]Anthony Tompkins, Fabio Ramos:
Fourier Feature Approximations for Periodic Kernels in Time-Series Modelling. AAAI 2018: 4155-4162 - [c112]Vitor Guizilini, Fabio Ramos:
Iterative Continuous Convolution for 3D Template Matching and Global Localization. AAAI 2018: 6493-6500 - [c111]Ransalu Senanayake, Fabio Ramos:
Building Continuous Occupancy Maps With Moving Robots. AAAI 2018: 6532-6539 - [c110]Vitor Guizilini, Fabio Ramos:
Fast 3D Modeling with Approximated Convolutional Kernels. CoRL 2018: 190-199 - [c109]Vitor Guizilini, Fabio Ramos:
Unpaired Learning of Dense Visual Depth Estimators for Urban Environments. CoRL 2018: 200-212 - [c108]Philippe Morere, Fabio Ramos:
Bayesian RL for Goal-Only Rewards. CoRL 2018: 386-398 - [c107]Ransalu Senanayake, Anthony Tompkins, Fabio Ramos:
Automorphing Kernels for Nonstationarity in Mapping Unstructured Environments. CoRL 2018: 443-455 - [c106]Rafael Possas, Sheila M. Pinto-Caceres, Fabio Ramos:
Egocentric Activity Recognition on a Budget. CVPR 2018: 5967-5976 - [c105]