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Diffusion generative modeling has become a promising approach for learning robotic manipulation tasks from stochastic human demonstrations.
Mira: Mental imagery for robotic affordances
Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, and Phillip Isola · 1927
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Normal distribution on the rotation group SO(3)
Dmitry I Nikolayev and Tatjana I Savyolov · 1970
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Normal distributions on SO(3)
TM Ivanova TI Savyolova · 1994
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Notes on stochastic processes on manifolds
Roger Brockett · 1997
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Regularized solutions of a nonlinear convolution equation on the euclidean group
Alexander B Kyatkin and Gregory S Chirikjian · 1998
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Engineering applications of noncommutative harmonic analysis: with emphasis on rotation and motion groups
Gregory S Chirikjian · 2000
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Stochastic models, information theory, and Lie groups, volume 2: Analytic methods and modern applications
Gregory S Chirikjian · 2011
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Reducing the barrier to entry of complex robotic software: a moveit! case study
David T Coleman, Ioan A Sucan, Sachin Chitta, and Nikolaus Correll · 2014
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Automatic generation and detection of highly reliable fiducial markers under occlusion
Sergio Garrido-Jurado, Rafael Muñoz-Salinas, Francisco José Madrid-Cuevas, and Manuel Jesús Marín-Jiménez · 2014
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Partial bi-invariance of SE(3) metrics
Gregory S Chirikjian · 2015
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Group theory in a nutshell for physicists
Anthony Zee · 2016
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Modern robotics
Kevin M Lynch and Frank C Park · 2017
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A mathematical introduction to robotic manipulation
Richard M Murray, Zexiang Li, and S Shankar Sastry · 2017
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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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A new approach to time-optimal path parameterization based on reachability analysis
Hung Pham and Quang-Cuong Pham · 2018
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Tensor field networks: Rotation-and translation-equivariant neural networks for 3d point clouds
Nathaniel Thomas, Tess Smidt, Steven Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, and Patrick Riley · 2018
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Open3D: A modern library for 3D data processing
Qian-Yi Zhou, Jaesik Park, and Vladlen Koltun · 2018
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Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation
Mathieu Labbé and François Michaud · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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SE(3)-transformers: 3d roto-translation equivariant attention networks
Fabian Fuchs, Daniel Worrall, Volker Fischer, and Max Welling · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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SAPIEN: A simulated part-based interactive environment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel X. Chang, Leonidas J. Guibas, and Hao Su · 2020
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Transporter networks: Rearranging the visual world for robotic manipulation
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, and Johnny Lee · 2020
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Alphafold2 and the future of structural biology
Patrick Cramer · 2021
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Vector neurons: A general framework for SO(3)-equivariant networks
Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacchi, and Leonidas J Guibas · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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E(n) equivariant graph neural networks
Vıctor Garcia Satorras, Emiel Hoogeboom, and Max Welling · 2021
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Learning to rearrange deformable cables, fabrics, and bags with goal-conditioned transporter networks
Daniel Seita, Pete Florence, Jonathan Tompson, Erwin Coumans, Vikas Sindhwani, Ken Goldberg, and Andy Zeng · 2021
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E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials
Simon Batzner, Albert Musaelian, Lixin Sun, Mario Geiger, Jonathan P Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E Smidt, and Boris Kozinsky · 2022
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Riemannian score-based generative modelling
Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson, James Thornton, Yee Whye Teh, and Arnaud Doucet · 2022
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EDGI: Equivariant diffusion for planning with embodied agents
Johann Brehmer, Joey Bose, Pim De Haan, and Taco Cohen · 2023
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Geometric algebra transformers
Johann Brehmer, Pim De Haan, Sönke Behrends, and Taco Cohen · 2023
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SE(3)-equivariant attention networks for shape reconstruction in function space
Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, and Kostas Daniilidis · 2023
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Planning with sequence models through iterative energy minimization
Hongyi Chen, Yilun Du, Yiye Chen, Joshua B Tenenbaum, and Patricio A Vela · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, and Shuran Song · 2023
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Local neural descriptor fields: Locally conditioned object representations for manipulation
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Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, and Tie-Yan Liu · 2022
Cited alongside, same era.
Independent SE(3)-equivariant models for end-to-end rigid protein docking
Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, and Andreas Krause · 2022
Cited alongside, same era.
e3nn: Euclidean neural networks, 2022
Mario Geiger and Tess Smidt · 2022
Cited alongside, same era.
Diffusion generative models on SO(3)
Yesukhei Jagvaral, Francois Lanusse, and Rachel Mandelbaum · 2022
Cited alongside, same era.
Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
Cited alongside, same era.
Denoising diffusion probabilistic models on SO(3) for rotational alignment
Adam Leach, Sebastian M Schmon, Matteo T Degiacomi, and Chris G Willcocks · 2022
Cited alongside, same era.
Equifold: Protein structure prediction with a novel coarse-grained structure representation
Jae Hyeon Lee, Payman Yadollahpour, Andrew Watkins, Nathan C Frey, Andrew Leaver-Fay, Stephen Ra, Kyunghyun Cho, Vladimir Gligorijević, Aviv Regev, and Richard Bonneau · 2022
Cited alongside, same era.
Ethan Chun, Yilun Du, Anthony Simeonov, Tomas Lozano-Perez, and Leslie Kaelbling · 2023
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Diffdock: Diffusion steps, twists, and turns for molecular docking
Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, and Tommi Jaakkola · 2023
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Banana: Banach fixed-point network for pointcloud segmentation with inter-part equivariance
Congyue Deng, Jiahui Lei, Bokui Shen, Kostas Daniilidis, and Leonidas Guibas · 2023
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Neuse: Neural se (3)-equivariant embedding for consistent spatial understanding with objects
Jiahui Fu, Yilun Du, Kurran Singh, Joshua B Tenenbaum, and John J Leonard · 2023
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Edge grasp network: A graph-based SE(3)-invariant approach to grasp detection
Haojie Huang, Dian Wang, Xupeng Zhu, Robin Walters, and Robert Platt · 2023
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Seil: Simulation-augmented equivariant imitation learning
Mingxi Jia, Dian Wang, Guanang Su, David Klee, Xupeng Zhu, Robin Walters, and Robert Platt · 2023
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Robotic manipulation learning with equivariant descriptor fields: Generative modeling, bi-equivariance, steerability, and locality
Jiwoo Kim, Hyunwoo Ryu, Jongeun Choi, Joohwan Seo, Nikhil Potu Surya Prakash, Ruolin Li, and Roberto Horowitz · 2023
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Statistical efficiency of score matching: The view from isoperimetry
Frederic Koehler, Alexander Heckett, and Andrej Risteski · 2023
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Symmetric models for visual force policy learning
Colin Kohler, Anuj Shrivatsav Srikanth, Eshan Arora, and Robert Platt · 2023
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Efem: Equivariant neural field expectation maximization for 3d object segmentation without scene supervision
Jiahui Lei, Congyue Deng, Karl Schmeckpeper, Leonidas Guibas, and Kostas Daniilidis · 2023
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Equiformer: Equivariant graph attention transformer for 3d atomistic graphs
Yi-Lun Liao and Tess Smidt · 2023
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Equiformerv2: Improved equivariant transformer for scaling to higher-degree representations
Yi-Lun Liao, Brandon Wood, Abhishek Das, and Tess Smidt · 2023
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Reorientdiff: Diffusion model based reorientation for object manipulation
Utkarsh Aashu Mishra and Yongxin Chen · 2023
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Imitating human behaviour with diffusion models
Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, and Sam Devlin · 2023
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Equivariant descriptor fields: SE(3)-equivariant energy-based models for end-to-end visual robotic manipulation learning
Hyunwoo Ryu, Hong in Lee, Jeong-Hoon Lee, and Jongeun Choi · 2023
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SE(3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Jan Peters, and Georgia Chalvatzaki · 2023
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SE(3) diffusion model with application to protein backbone generation
Jason Yim, Brian L Trippe, Valentin De Bortoli, Emile Mathieu, Arnaud Doucet, Regina Barzilay, and Tommi Jaakkola · 2023
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SE(3) frame equivariance in dynamics modeling and reinforcement learning
Linfeng Zhao, Jung Yeon Park, Xupeng Zhu, Robin Walters, and Lawson LS Wong · 2023
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E2pn: Efficient SE(3)-equivariant point network
Minghan Zhu, Maani Ghaffari, William A Clark, and Huei Peng · 2023
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