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Most set prediction models in deep learning use set-equivariant operations, but they actually operate on multisets.
The Hungarian method for the assignment problem
Harold W Kuhn · 1955
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Robust Estimation of a Location Parameter
Peter J. Huber · 1964
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A method for solving the convex programming problem with convergence rate o ( 1 / k 2 ) o(1/k^{2})
Yurii E. Nesterov · 1983
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Deep learning via hessian-free optimization
James Martens · 2010
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Unbiased look at dataset bias
Antonio Torralba and Alexei A. Efros · 2011
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Face recognition performance: Role of demographic information
Brendan F. Klare, Mark J. Burge, Joshua C. Klontz, Richard W. Vorder Bruegge, and Anil K. Jain · 2012
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The implicit function theorem: history, theory, and applications
Steven G Krantz and Harold R Parks · 2012
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton · 2013
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TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dandelion Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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Stephen Gould, Basura Fernando, Anoop Cherian, Peter Anderson, Rodrigo Santa Cruz, and Edison Guo · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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End-to-end people detection in crowded scenes
Russell Stewart and Mykhaylo Andriluka · 2016
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Order matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, and Manjunath Kudlur · 2016
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Optnet: Differentiable optimization as a layer in neural networks
Brandon Amos and J Zico Kolter · 2017
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End-to-end learning for structured prediction energy networks
David Belanger, Bishan Yang, and Andrew. McCallum · 2017
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C Lawrence Zitnick, and Ross Girshick · 2017
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, Michael Bernstein, and Li Fei-Fei · 2017
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A simple neural network module for relational reasoning
Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, and Tim Lillicrap · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Scene graph generation by iterative message passing
Danfei Xu, Yuke Zhu, Christopher Choy, and Li Fei-Fei · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ R Salakhutdinov, and Alexander J Smola · 2017
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Learning representations and generative models for 3D point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas J Guibas · 2018
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Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning
Qimai Li, Zhichao Han, and Xiao-Ming Wu · 2018
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Learning deep generative models of graphs
Yujia Li, Oriol Vinyals, Chris Dyer, Razvan Pascanu, and Peter Battaglia · 2018
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Super-efficiency of automatic differentiation for functions defined as a minimum
Pierre Ablin, Gabriel Peyré, and Thomas Moreau · 2020
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Multiscale deep equilibrium models
Shaojie Bai, Vladlen Koltun, and J. Zico Kolter · 2020
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Experiment tracking with weights and biases, 2020
Lukas Biewald · 2020
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Deepsvg: A hierarchical generative network for vector graphics animation
Alexandre Carlier, Martin Danelljan, Alexandre Alahi, and Radu Timofte · 2020
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Implicit graph neural networks
Fangda Gu, Heng Chang, Wenwu Zhu, Somayeh Sojoudi, and Laurent El Ghaoui · 2020
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GraphVAE: Towards generation of small graphs using variational autoencoders
Martin Simonovsky and Nikos Komodakis · 2018
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How powerful are graph neural networks?
Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka · 2018
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Differentiable convex optimization layers
A. Agrawal, B. Amos, S. Barratt, S. Boyd, S. Diamond, and Z. Kolter · 2019
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Deep equilibrium models
Shaojie Bai, J. Zico Kolter, and Vladlen Koltun · 2019
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Does object recognition work for everyone
Terrance DeVries, Ishan Misra, Changhan Wang, and Laurens van der Maaten · 2019
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End-to-End Neural Speaker Diarization with Permutation-free Objectives
Yusuke Fujita, Naoyuki Kanda, Shota Horiguchi, Kenji Nagamatsu, and Shinji Watanabe · 2019
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Better set representations for relational reasoning
Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, and Austin Benson · 2020
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Conditional set generation with transformers
Adam R Kosiorek, Hyunjik Kim, and Danilo J Rezende · 2020
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Object-centric learning with slot attention
Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, and Thomas Kipf · 2020
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Differentiating through the fréchet mean
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, and Christopher De Sa · 2020
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Learn to predict sets using feed-forward neural networks
Hamid Rezatofighi, Roman Kaskman, Farbod T Motlagh, Qinfeng Shi, Anton Milan, Daniel Cremers, Laura Leal-Taixé, and Ian Reid · 2020
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Face recognition: Too bias, or not too bias?
Joseph P. Robinson, Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner · 2020
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FSPool: Learning set representations with featurewise sort pooling
Yan Zhang, Jonathon Hare, and Adam Prügel-Bennett · 2020
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Efficient and modular implicit differentiation
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, and Jean-Philippe Vert · 2021
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Implicit deep learning
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Diffusion probabilistic models for 3d point cloud generation
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A survey on bias and fairness in machine learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan · 2021
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JFB: Jacobian-free backpropagation for implicit networks
Samy Wu Fung, Howard Heaton, Qiuwei Li, Daniel McKenzie, Stanley Osher, and Wotao Yin · 2022
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