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Equivariance has gained strong interest as a desirable network property that inherently ensures robust generalization.
Hierarchical grouping to optimize an objective function
Joe H Ward Jr · 1963
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Working memory
Alan Baddeley · 1992
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Learning task-dependent distributed representations by backpropagation through structure
Christoph Goller and Andreas Kuchler · 1996
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Working memory: Theories, models, and controversies
Alan Baddeley · 2012
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Nice: Non-linear independent components estimation
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Rich feature hierarchies for accurate object detection and semantic segmentation
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik · 2014
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, et al · 2015
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Fast r-cnn
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Bridging the gaps between residual learning, recurrent neural networks and visual cortex
Qianli Liao and Tomaso Poggio · 2016
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Cnn-rnn: A unified framework for multi-label image classification
Jiang Wang, Yi Yang, Junhua Mao, Zhiheng Huang, Chang Huang, and Wei Xu · 2016
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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3dcnn-dqn-rnn: A deep reinforcement learning framework for semantic parsing of large-scale 3d point clouds
Fangyu Liu, Shuaipeng Li, Liqiang Zhang, Chenghu Zhou, Rongtian Ye, Yuebin Wang, and Jiwen Lu · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 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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Banach contraction principle and applications
Praveen Agarwal, Mohamed Jleli, Bessem Samet, Praveen Agarwal, Mohamed Jleli, and Bessem Samet · 2018
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Pointflownet: Learning representations for 3d scene flow estimation from point clouds
Aseem Behl, Despoina Paschalidou, Simon Donné, and Andreas Geiger · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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On the generalization of equivariance and convolution in neural networks to the action of compact groups
Risi Kondor and Shubhendu Trivedi · 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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Lipschitz regularity of deep neural networks: analysis and efficient estimation
Aladin Virmaux and Kevin Scaman · 2018
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3d recurrent neural networks with context fusion for point cloud semantic segmentation
Xiaoqing Ye, Jiamao Li, Hexiao Huang, Liang Du, and Xiaolin Zhang · 2018
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Deep part induction from articulated object pairs
Li Yi, Haibin Huang, Difan Liu, Evangelos Kalogerakis, Hao Su, and Leonidas Guibas · 2018
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Bae-net: Branched autoencoder for shape co-segmentation
Zhiqin Chen, Kangxue Yin, Matthew Fisher, Siddhartha Chaudhuri, and Hao Zhang · 2019
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A general theory of equivariant cnns on homogeneous spaces
Taco S Cohen, Mario Geiger, and Maurice Weiler · 2019
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Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior
Kohitij Kar, Jonas Kubilius, Kailyn Schmidt, Elias B Issa, and James J DiCarlo · 2019
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Flownet3d: Learning scene flow in 3d point clouds
Xingyu Liu, Charles R Qi, and Leonidas J Guibas · 2019
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Meteornet: Deep learning on dynamic 3d point cloud sequences
Xingyu Liu, Mengyuan Yan, and Jeannette Bohg · 2019
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Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding
Kaichun Mo, Shilin Zhu, Angel X Chang, Li Yi, Subarna Tripathi, Leonidas J Guibas, and Hao Su · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Adversarial lipschitz regularization
Dávid Terjék · 2019
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Shape2motion: Joint analysis of motion parts and attributes from 3d shapes
Xiaogang Wang, Bin Zhou, Yahao Shi, Xiaowu Chen, Qinping Zhao, and Kai Xu · 2019
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
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Homogeneous vector bundles and g-equivariant convolutional neural networks
Jimmy Aronsson · 2022
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Vn-transformer: Rotation-equivariant attention for vector neurons
Serge Assaad, Carlton Downey, Rami Al-Rfou, Nigamaa Nayakanti, and Ben Sapp · 2022
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End-to-end algorithm synthesis with recurrent networks: Logical extrapolation without overthinking
Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, and Tom Goldstein · 2022
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Se (3)-equivariant attention networks for shape reconstruction in function space
Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, and Kostas Daniilidis · 2022
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4dcontrast: Contrastive learning with dynamic correspondences for 3d scene understanding
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Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 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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Nonparametric object and parts modeling with lie group dynamics
David S Hayden, Jason Pacheco, and John W Fisher · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Pointgroup: Dual-set point grouping for 3d instance segmentation
Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, and Jiaya Jia · 2020
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Flot: Scene flow on point clouds guided by optimal transport
Gilles Puy, Alexandre Boulch, and Renaud Marlet · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Yujin Chen, Matthias Nießner, and Angela Dai · 2022
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Robust change detection based on neural descriptor fields
Jiahui Fu, Yilun Du, Kurran Singh, Joshua B Tenenbaum, and John J Leonard · 2022
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Neural contact fields: Tracking extrinsic contact with tactile sensing
Carolina Higuera, Siyuan Dong, Byron Boots, and Mustafa Mukadam · 2022
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Dynamic 3d scene analysis by point cloud accumulation
Shengyu Huang, Zan Gojcic, Jiahui Huang, Andreas Wieser, and Konrad Schindler · 2022
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Ditto: Building digital twins of articulated objects from interaction
Zhenyu Jiang, Cheng-Chun Hsu, and Yuke Zhu · 2022
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Shape-pose disentanglement using se (3)-equivariant vector neurons
Oren Katzir, Dani Lischinski, and Daniel Cohen-Or · 2022
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Cadex: Learning canonical deformation coordinate space for dynamic surface representation via neural homeomorphism
Jiahui Lei and Kostas Daniilidis · 2022
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Directed weight neural networks for protein structure representation learning
Jiahan Li, Shitong Luo, Congyue Deng, Chaoran Cheng, Jiaqi Guan, Leonidas Guibas, Jian Peng, and Jianzhu Ma · 2022
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Coarse-to-fine point cloud registration with se (3)-equivariant representations
Cheng-Wei Lin, Tung-I Chen, Hsin-Ying Lee, Wen-Chin Chen, and Winston H Hsu · 2022
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So (3)-pose: So (3)-equivariance learning for 6d object pose estimation
Haoran Pan, Jun Zhou, Yuanpeng Liu, Xuequan Lu, Weiming Wang, Xuefeng Yan, and Mingqiang Wei · 2022
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Hyunwoo Ryu, Jeong-Hoon Lee, Hong-in Lee, and Jongeun Choi · 2022
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Condor: Self-supervised canonicalization of 3d pose for partial shapes
Rahul Sajnani, Adrien Poulenard, Jivitesh Jain, Radhika Dua, Leonidas J Guibas, and Srinath Sridhar · 2022
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Neural descriptor fields: Se (3)-equivariant object representations for manipulation
Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, and Vincent Sitzmann · 2022
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Ogc: Unsupervised 3d object segmentation from rigid dynamics of point clouds
Ziyang Song and Bo Yang · 2022
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4d unsupervised object discovery
Yuqi Wang, Yuntao Chen, and ZHAO-XIANG ZHANG · 2022
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Neural grasp distance fields for robot manipulation
Thomas Weng, David Held, Franziska Meier, and Mustafa Mukadam · 2022
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Unified fourier-based kernel and nonlinearity design for equivariant networks on homogeneous spaces
Yinshuang Xu, Jiahui Lei, Edgar Dobriban, and Kostas Daniilidis · 2022
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Useek: Unsupervised se (3)-equivariant 3d keypoints for generalizable manipulation
Zhengrong Xue, Zhecheng Yuan, Jiashun Wang, Xueqian Wang, Yang Gao, and Huazhe Xu · 2022
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Rotationally equivariant 3d object detection
Hong-Xing Yu, Jiajun Wu, and Li Yi · 2022
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Rethinking lipschitz neural networks and certified robustness: A boolean function perspective
Bohang Zhang, Du Jiang, Di He, and Liwei Wang · 2022
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Correspondence-free point cloud registration with so (3)-equivariant implicit shape representations
Minghan Zhu, Maani Ghaffari, and Huei Peng · 2022
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Jiahui Lei, Congyue Deng, Karl Schmeckpeper, Leonidas Guibas, and Kostas Daniilidis · 2023
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Lego-net: Learning regular rearrangements of objects in rooms
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