Michael Bloesch

51 papers A* 10A 5C 1Misc 3Journal 29Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Learning from negative feedback, or positive feedback or both. ICLR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Michael Bloesch, Rishabh Joshi, Thomas Lampe, Junhyuk Oh, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2025	J	`jnl`	Value from Observations: Towards Large-Scale Imitation Learning via Self-Improvement. CoRR Michael Bloesch, Markus Wulfmeier, Philemon Brakel, Todor Davchev, Martina Zambelli, Jost Tobias Springenberg, Abbas Abdolmaleki, William F. Whitney, Nicolas Heess, Roland Hafner, Martin A. Riedmiller
2024	A*	`conf`	Imitating Language via Scalable Inverse Reinforcement Learning. NeurIPS Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller
2024	J	`jnl`	Imitating Language via Scalable Inverse Reinforcement Learning. CoRR Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Maria Elisabeth Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller
2024	J	`jnl`	Learning agile soccer skills for a bipedal robot with deep reinforcement learning. Sci. Robotics Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
2024	A*	`conf`	Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. ICRA Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle, Sandy H. Huang, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin A. Riedmiller
2024	A*	`conf`	Offline Actor-Critic Reinforcement Learning Scales to Large Models. ICML Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2024	J	`jnl`	Offline Actor-Critic Reinforcement Learning Scales to Large Models. CoRR Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2024	J	`jnl`	Preference Optimization as Probabilistic Inference. CoRR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Rishabh Joshi, Junhyuk Oh, Michael Bloesch, Thomas Lampe, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2023	J	`jnl`	Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. CoRR Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
2023	J	`jnl`	Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. CoRR Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle, Sandy H. Huang, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin A. Riedmiller
2022	J	`jnl`	Dense RGB-D-Inertial SLAM with Map Deformations. CoRR Tristan Laidlow, Michael Bloesch, Wenbin Li, Stefan Leutenegger
2022	J	`jnl`	The Challenges of Exploration for Offline Reinforcement Learning. CoRR Nathan Lambert, Markus Wulfmeier, William F. Whitney, Arunkumar Byravan, Michael Bloesch, Vibhavari Dasagi, Tim Hertweck, Martin A. Riedmiller
2021	J	`jnl`	Rethinking Exploration for Sample-Efficient Policy Learning. CoRR William F. Whitney, Michael Bloesch, Jost Tobias Springenberg, Abbas Abdolmaleki, Martin A. Riedmiller
2021	Misc	`conf`	Towards Real Robot Learning in the Wild: A Case Study in Bipedal Locomotion. CoRL Michael Bloesch, Jan Humplik, Viorica Patraucean, Roland Hafner, Tuomas Haarnoja, Arunkumar Byravan, Noah Yamamoto Siegel, Saran Tunyasuvunakool, Federico Casarini, Nathan Batchelor, Francesco Romano, Stefano Saliceti, Martin A. Riedmiller, S. M. Ali Eslami, Nicolas Heess
2020	A*	`conf`	Comparing View-Based and Map-Based Semantic Labelling in Real-Time SLAM. ICRA Zoe Landgraf, Fabian Falck, Michael Bloesch, Stefan Leutenegger, Andrew J. Davison
2020	J	`jnl`	Comparing View-Based and Map-Based Semantic Labelling in Real-Time SLAM. CoRR Zoe Landgraf, Fabian Falck, Michael Bloesch, Stefan Leutenegger, Andrew J. Davison
2020	J	`jnl`	Simple Sensor Intentions for Exploration. CoRR Tim Hertweck, Martin A. Riedmiller, Michael Bloesch, Jost Tobias Springenberg, Noah Y. Siegel, Markus Wulfmeier, Roland Hafner, Nicolas Heess
2020	Misc	`conf`	Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion. CoRL Roland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin A. Riedmiller
2020	J	`jnl`	Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion. CoRR Roland Hafner, Tim Hertweck, Philipp Klöppner, Michael Bloesch, Michael Neunert, Markus Wulfmeier, Saran Tunyasuvunakool, Nicolas Heess, Martin A. Riedmiller
2019	A*	`conf`	KO-Fusion: Dense Visual SLAM with Tightly-Coupled Kinematic and Odometric Tracking. ICRA Charlie Houseago, Michael Bloesch, Stefan Leutenegger
2019	A*	`conf`	Learning Meshes for Dense Visual SLAM. ICCV Michael Bloesch, Tristan Laidlow, Ronald Clark, Stefan Leutenegger, Andrew J. Davison
2019	A*	`conf`	MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM. ICRA Binbin Xu, Wenbin Li, Dimos Tzoumanikas, Michael Bloesch, Andrew J. Davison, Stefan Leutenegger
2019	A	`conf`	Matching Features without Descriptors: Implicitly Matched Interest Points. BMVC Titus Cieslewski, Michael Bloesch, Davide Scaramuzza
2019	A*	`conf`	SceneCode: Monocular Dense Semantic Reconstruction Using Learned Encoded Scene Representations. CVPR Shuaifeng Zhi, Michael Bloesch, Stefan Leutenegger, Andrew J. Davison
2019	J	`jnl`	SceneCode: Monocular Dense Semantic Reconstruction using Learned Encoded Scene Representations. CoRR Shuaifeng Zhi, Michael Bloesch, Stefan Leutenegger, Andrew J. Davison
2018	J	`jnl`	A framework for maximum likelihood parameter identification applied on MAVs. J. Field Robotics Michael Burri, Michael Bloesch, Zachary Taylor, Roland Siegwart, Juan I. Nieto
2018	J	`jnl`	Build Your Own Visual-Inertial Drone: A Cost-Effective and Open-Source Autonomous Drone. IEEE Robotics Autom. Mag. Inkyu Sa, Mina Kamel, Michael Burri, Michael Bloesch, Raghav Khanna, Marija Popovic, Juan I. Nieto, Roland Siegwart
2018	A*	`conf`	CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM. CVPR Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, Andrew J. Davison
2018	J	`jnl`	CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAM. CoRR Michael Bloesch, Jan Czarnowski, Ronald Clark, Stefan Leutenegger, Andrew J. Davison
2018	—	`conf`	Fusion++: Volumetric Object-Level SLAM. 3DV John McCormac, Ronald Clark, Michael Bloesch, Andrew J. Davison, Stefan Leutenegger
2018	J	`jnl`	Fusion++: Volumetric Object-Level SLAM. CoRR John McCormac, Ronald Clark, Michael Bloesch, Andrew J. Davison, Stefan Leutenegger
2018	J	`jnl`	LS-Net: Learning to Solve Nonlinear Least Squares for Monocular Stereo. CoRR Ronald Clark, Michael Bloesch, Jan Czarnowski, Stefan Leutenegger, Andrew J. Davison
2018	—	`conf`	Learning to Solve Nonlinear Least Squares for Monocular Stereo. ECCV (8) Ronald Clark, Michael Bloesch, Jan Czarnowski, Stefan Leutenegger, Andrew J. Davison
2018	J	`jnl`	MID-Fusion: Octree-based Object-Level Multi-Instance Dynamic SLAM. CoRR Binbin Xu, Wenbin Li, Dimos Tzoumanikas, Michael Bloesch, Andrew J. Davison, Stefan Leutenegger
2018	J	`jnl`	Matching Features without Descriptors: Implicitly Matched Interest Points (IMIPs). CoRR Titus Cieslewski, Michael Bloesch, Davide Scaramuzza
2018	J	`jnl`	Probabilistic Terrain Mapping for Mobile Robots With Uncertain Localization. IEEE Robotics Autom. Lett. Peter Fankhauser, Michael Bloesch, Marco Hutter
2018	Misc	`conf`	Task-Embedded Control Networks for Few-Shot Imitation Learning. CoRL Stephen James, Michael Bloesch, Andrew J. Davison
2018	J	`jnl`	Task-Embedded Control Networks for Few-Shot Imitation Learning. CoRR Stephen James, Michael Bloesch, Andrew J. Davison
2018	J	`jnl`	The Two-State Implicit Filter Recursive Estimation for Mobile Robots. IEEE Robotics Autom. Lett. Michael Bloesch, Michael Burri, Hannes Sommer, Roland Siegwart, Marco Hutter
2018	J	`jnl`	Why and How to Avoid the Flipped Quaternion Multiplication. CoRR Hannes Sommer, Igor Gilitschenski, Michael Bloesch, Stephan Weiss, Roland Siegwart, Juan I. Nieto
2017	J	`jnl`	Build your own visual-inertial odometry aided cost-effective and open-source autonomous drone. CoRR Inkyu Sa, Mina Kamel, Michael Burri, Michael Bloesch, Raghav Khanna, Marija Popovic, Juan I. Nieto, Roland Siegwart
2017	A	`conf`	Dense RGB-D-inertial SLAM with map deformations. IROS Tristan Laidlow, Michael Bloesch, Wenbin Li, Stefan Leutenegger
2017	J	`jnl`	Iterated extended Kalman filter based visual-inertial odometry using direct photometric feedback. Int. J. Robotics Res. Michael Bloesch, Michael Burri, Sammy Omari, Marco Hutter, Roland Siegwart
2016	J	`jnl`	A Primer on the Differential Calculus of 3D Orientations. CoRR Michael Bloesch, Hannes Sommer, Tristan Laidlow, Michael Burri, Gabriel Nützi, Peter Fankhauser, Dario Bellicoso, Christian Gehring, Stefan Leutenegger, Marco Hutter, Roland Siegwart
2016	A	`conf`	ANYmal - a highly mobile and dynamic quadrupedal robot. IROS Marco Hutter, Christian Gehring, Dominic Jud, Andreas Lauber, C. Dario Bellicoso, Vassilios Tsounis, Jemin Hwangbo, Karen Bodie, Peter Fankhauser, Michael Bloesch, Remo Diethelm, Samuel Bachmann, Amir Melzer, Mark A. Höpflinger
2016	C	`conf`	An open source, fiducial based, visual-inertial motion capture system. FUSION Michael Neunert, Michael Bloesch, Jonas Buchli
2016	A	`conf`	Collaborative navigation for flying and walking robots. IROS Peter Fankhauser, Michael Bloesch, Philipp Krusi, Remo Diethelm, Martin Wermelinger, Thomas Schneider, Marcin Dymczyk, Marco Hutter, Roland Siegwart
2016	A	`conf`	Generalized information filtering for MAV parameter estimation. IROS Michael Burri, Michael Bloesch, Dominik Schindler, Igor Gilitschenski, Zachary Taylor, Roland Siegwart
2016	J	`jnl`	Practice Makes Perfect: An Optimization-Based Approach to Controlling Agile Motions for a Quadruped Robot. IEEE Robotics Autom. Mag. Christian Gehring, Stelian Coros, Marco Hutter, Carmine Dario Bellicoso, Huub Heijnen, Remo Diethelm, Michael Bloesch, Peter Fankhauser, Jemin Hwangbo, Mark A. Hoepflinger, Roland Siegwart
2016	—	`conf`	gvnn: Neural Network Library for Geometric Computer Vision. ECCV Workshops (3) Ankur Handa, Michael Bloesch, Viorica Patraucean, Simon Stent, John McCormac, Andrew J. Davison