Ramos, Fabio

49 publications

NeurIPS 2025 Diversifying Parallel Ergodic Search: A Signature Kernel Evolution Strategy Sreevardhan Sirigiri, Christian Hughes, Ian Abraham, Fabio Ramos

ICLR 2025 HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation Yi Li, Yuquan Deng, Jesse Zhang, Joel Jang, Marius Memmel, Caelan Reed Garrett, Fabio Ramos, Dieter Fox, Anqi Li, Abhishek Gupta, Ankit Goyal

AISTATS 2024 Fast Fourier Bayesian Quadrature Houston Warren, Fabio Ramos

CoRL 2024 Gentle Manipulation of Tree Branches: A Contact-Aware Policy Learning Approach Jay Jacob, Shizhe Cai, Paulo Vinicius Koerich Borges, Tirthankar Bandyopadhyay, Fabio Ramos

L4DC 2024 Signatures Meet Dynamic Programming: Generalizing Bellman Equations for Trajectory Following Motoya Ohnishi, Iretiayo Akinola, Jie Xu, Ajay Mandlekar, Fabio Ramos

UAI 2024 Stein Random Feature Regression Houston Warren, Rafael Oliveira, Fabio Ramos

CoRL 2023 Ready, Set, Plan! Planning to Goal Sets Using Generalized Bayesian Inference Jana Pavlasek, Stanley Robert Lewis, Balakumar Sundaralingam, Fabio Ramos, Tucker Hermans

ICLR 2022 Accelerated Policy Learning with Parallel Differentiable Simulation Jie Xu, Viktor Makoviychuk, Yashraj Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, Miles Macklin

L4DC 2022 Adaptive Model Predictive Control by Learning Classifiers Rel Guzman, Rafael Oliveira, Fabio Ramos

CoRL 2022 Bayesian Object Models for Robotic Interaction with Differentiable Probabilistic Programming Krishna Murthy Jatavallabhula, Miles Macklin, Dieter Fox, Animesh Garg, Fabio Ramos

L4DC 2022 Diffeomorphic Transforms for Generalised Imitation Learning Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos

UAI 2022 Generalized Bayesian Quadrature with Spectral Kernels Houston Warren, Rafael Oliveira, Fabio Ramos

ICML 2022 Learning Efficient and Robust Ordinary Differential Equations via Invertible Neural Networks Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos

NeurIPSW 2022 Learning Successor Feature Representations to Train Robust Policies for Multi-Task Learning Melissa Mozifian, Dieter Fox, David Meger, Fabio Ramos, Animesh Garg

NeurIPSW 2022 Variance Reduction in Off-Policy Deep Reinforcement Learning Using Spectral Normalization Payal Bawa, Rafael Oliveira, Fabio Ramos

ICML 2021 BORE: Bayesian Optimization by Density-Ratio Estimation Louis C Tiao, Aaron Klein, Matthias W Seeger, Edwin V. Bonilla, Cedric Archambeau, Fabio Ramos

UAI 2021 No-Regret Approximate Inference via Bayesian Optimisation Rafael Oliveira, Lionel Ott, Fabio Ramos

CoRL 2021 Parallelised Diffeomorphic Sampling-Based Motion Planning Tin Lai, Weiming Zhi, Tucker Hermans, Fabio Ramos

CoRL 2021 STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation Mohak Bhardwaj, Balakumar Sundaralingam, Arsalan Mousavian, Nathan D. Ratliff, Dieter Fox, Fabio Ramos, Byron Boots

CoRL 2020 A User’s Guide to Calibrating Robotic Simulators Bhairav Mehta, Ankur Handa, Dieter Fox, Fabio Ramos

UAI 2020 Active Learning of Conditional Mean Embeddings via Bayesian Optimisation Sayak Ray Chowdhury, Rafael Oliveira, Fabio Ramos

L4DC 2020 Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable Dynamical Systems Muhammad Asif Rana, Anqi Li, Dieter Fox, Byron Boots, Fabio Ramos, Nathan Ratliff

CoRL 2020 STReSSD: Sim-to-Real from Sound for Stochastic Dynamics Carolyn Matl, Yashraj Narang, Dieter Fox, Ruzena Bajcsy, Fabio Ramos

CoRL 2020 Stein Variational Model Predictive Control Alexander Lambert, Fabio Ramos, Byron Boots, Dieter Fox, Adam Fishman

ICML 2019 Bayesian Deconditional Kernel Mean Embeddings Kelvin Hsu, Fabio Ramos

AISTATS 2019 Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference Kelvin Hsu, Fabio Ramos

AISTATS 2019 Bayesian Optimisation Under Uncertain Inputs Rafael Oliveira, Lionel Ott, Fabio Ramos

AISTATS 2019 Black Box Quantiles for Kernel Learning Anthony Tompkins, Ransalu Senanayake, Philippe Morere, Fabio Ramos

CoRL 2019 Kernel Trajectory Maps for Multi-Modal Probabilistic Motion Prediction Weiming Zhi, Lionel Ott, Fabio Ramos

UAI 2019 Periodic Kernel Approximation by Index Set Fourier Series Features Anthony Tompkins, Fabio Ramos

CoRL 2018 Automorphing Kernels for Nonstationarity in Mapping Unstructured Environments Ransalu Senanayake, Anthony Tompkins, Fabio Ramos

CoRL 2018 Bayesian RL for Goal-Only Rewards Philippe Morere, Fabio Ramos

AAAI 2018 Building Continuous Occupancy Maps with Moving Robots Ransalu Senanayake, Fabio Ramos

CoRL 2018 Fast 3D Modeling with Approximated Convolutional Kernels Vitor Guizilini, Fabio Ramos

AAAI 2018 Fourier Feature Approximations for Periodic Kernels in Time-Series Modelling Anthony Tompkins, Fabio Ramos

ECML-PKDD 2018 Hyperparameter Learning for Conditional Kernel Mean Embeddings with Rademacher Complexity Bounds Kelvin Hsu, Richard Nock, Fabio Ramos

AAAI 2018 Iterative Continuous Convolution for 3D Template Matching and Global Localization Vitor Guizilini, Fabio Ramos

CoRL 2018 Unpaired Learning of Dense Visual Depth Estimators for Urban Environments Vitor Guizilini, Fabio Ramos

CoRL 2017 Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping Ransalu Senanayake, Fabio Ramos

MLJ 2016 Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection Markus Schneider, Wolfgang Ertel, Fabio Ramos

AAAI 2016 Predicting Spatio-Temporal Propagation of Seasonal Influenza Using Variational Gaussian Process Regression Ransalu Senanayake, Simon Timothy O'Callaghan, Fabio Ramos

AAAI 2015 Variational Inference for Nonparametric Bayesian Quantile Regression Sachinthaka Abeywardana, Fabio Ramos

UAI 2014 Sequential Bayesian Optimisation for Spatial-Temporal Monitoring Román Marchant, Fabio Ramos, Scott Sanner

IJCAI 2013 Bayesian Joint Inversions for the Exploration of Earth Resources Alistair Reid, Simon Timothy O'Callaghan, Edwin V. Bonilla, Lachlan McCalman, Tim Rawling, Fabio Ramos

AAAI 2012 Learning Non-Stationary Space-Time Models for Environmental Monitoring Sahil Garg, Amarjeet Singh, Fabio Ramos

UAI 2011 Distributed Anytime MAP Inference Joop van de Ven, Fabio Ramos

IJCAI 2011 Learning 3D Geological Structure from Drill-Rig Sensors for Automated Mining Sildomar T. Monteiro, Joop van de Ven, Fabio Ramos, Peter Hatherly

IJCAI 2011 Multi-Kernel Gaussian Processes Arman Melkumyan, Fabio Ramos

IJCAI 2009 A Sparse Covariance Function for Exact Gaussian Process Inference in Large Datasets Arman Melkumyan, Fabio Ramos