OptNet: Differentiable Optimization as a Layer in Neural Networks

1 March 2017

J. Zico Kolter

Papers citing "OptNet: Differentiable Optimization as a Layer in Neural Networks"

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Title
Lagrangian Duality for Constrained Deep Learning Ferdinando Fioretto Pascal Van Hentenryck Terrence W.K. Mak Cuong Tran Federico Baldo M. Lombardi PINN 62 84 0 26 Jan 2020
Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics David Millard Eric Heiden Shubham Agrawal Gaurav Sukhatme AI4CE 77 13 0 22 Jan 2020
Learning to Control PDEs with Differentiable Physics Philipp Holl V. Koltun Nils Thuerey AI4CE PINN 87 189 0 21 Jan 2020
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects Fredrik D. Johansson Uri Shalit Nathan Kallus David Sontag CML OOD 128 100 0 21 Jan 2020
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction Vlad Niculae André F. T. Martins TPM 106 19 0 13 Jan 2020
Infinite-Horizon Differentiable Model Predictive Control Sebastian East Marco Gallieri Jonathan Masci Jan Koutník M. Cannon 47 34 0 07 Jan 2020
Lossless Compression of Deep Neural Networks Thiago Serra Abhinav Kumar Srikumar Ramalingam 108 57 0 01 Jan 2020
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework Wanxin Jin Zhaoran Wang Zhuoran Yang Shaoshuai Mou 96 80 0 30 Dec 2019
Memory-efficient Learning for Large-scale Computational Imaging -- NeurIPS deep inverse workshop Michael R. Kellman Jonathan I. Tamir E. Bostan Michael Lustig Laura Waller SupR 96 58 0 11 Dec 2019
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning Sanket Shah Arunesh Sinha Pradeep Varakantham Andrew Perrault Milind Tambe 77 12 0 20 Nov 2019
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 104 669 0 28 Oct 2019
gradSLAM: Automagically differentiable SLAM Krishna Murthy Jatavallabhula Soroush Saryazdi Ganesh Iyer Liam Paull 86 57 0 23 Oct 2019
Automatically Batching Control-Intensive Programs for Modern Accelerators Alexey Radul Brian Patton D. Maclaurin Matthew D. Hoffman Rif A. Saurous 60 12 0 23 Oct 2019
Coercing Machine Learning to Output Physically Accurate Results Z. Geng Dan Johnson Ronald Fedkiw 3DH 53 37 0 21 Oct 2019
The Differentiable Cross-Entropy Method Brandon Amos Denis Yarats 131 54 0 27 Sep 2019
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization offers Significant Performance and Efficiency Gains Sathya Ravi Abhay Venkatesh G. Fung Vikas Singh 48 3 0 26 Sep 2019
From feature selection to continuous optimization H. Rakhshani L. Idoumghar Julien Lepagnot Mathieu Brévilliers 26 1 0 20 Sep 2019
End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization Bo Chen Álvaro Parra Jiewei Cao Nan Li Tat-Jun Chin 3DH 95 93 0 13 Sep 2019
Deep Declarative Networks: A New Hope Stephen Gould Leonid Sigal Dylan Campbell AI4CE 98 108 0 11 Sep 2019
Meta-Learning with Implicit Gradients Aravind Rajeswaran Chelsea Finn Sham Kakade Sergey Levine 254 859 0 10 Sep 2019
Deep Equilibrium Models Shaojie Bai J. Zico Kolter V. Koltun 112 674 0 03 Sep 2019
Adaptively Sparse Transformers Gonçalo M. Correia Vlad Niculae André F. T. Martins 141 257 0 30 Aug 2019
Implicit Deep Learning L. Ghaoui Fangda Gu Bertrand Travacca Armin Askari Alicia Y. Tsai AI4CE 66 182 0 17 Aug 2019
Parametric Majorization for Data-Driven Energy Minimization Methods Jonas Geiping Michael Moeller 134 4 0 17 Aug 2019
Differentiable Gaussian Process Motion Planning M. Bhardwaj Byron Boots Mustafa Mukadam 70 63 0 22 Jul 2019
MIPaaL: Mixed Integer Program as a Layer Aaron Ferber Bryan Wilder B. Dilkina Milind Tambe 112 148 0 12 Jul 2019
Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction Tak Ming Wong M. Kahl P. Bolívar A. Kolb Michael Möller 30 8 0 02 Jul 2019
The Limited Multi-Label Projection Layer Brandon Amos V. Koltun J. Zico Kolter 95 36 0 20 Jun 2019
Bilevel Optimization for Planning through Contact: A Semidirect Method Benoit Landry Joseph Lorenzetti Zachary Manchester Marco Pavone 77 15 0 10 Jun 2019
Machine Learning and System Identification for Estimation in Physical Systems Fredrik Bagge Carlson OOD 54 5 0 05 Jun 2019
End to end learning and optimization on graphs Bryan Wilder Eric Ewing B. Dilkina Milind Tambe GNN 86 107 0 31 May 2019
Deep Learning for Distributed Optimization: Applications to Wireless Resource Management Hoon Lee Sang Hyun Lee Tony Q.S. Quek 71 94 0 31 May 2019
SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver Po-Wei Wang P. Donti Bryan Wilder Zico Kolter LRM NAI 90 265 0 29 May 2019
Differentiable Algorithm Networks for Composable Robot Learning Peter Karkus Xiao Ma David Hsu L. Kaelbling Wee Sun Lee Tomas Lozano-Perez 64 71 0 28 May 2019
Generalization Bounds in the Predict-then-Optimize Framework Othman El Balghiti Adam N. Elmachtoub Paul Grigas Ambuj Tewari 93 69 0 27 May 2019
Interactive Differentiable Simulation Eric Heiden David Millard Hejia Zhang Gaurav Sukhatme OOD AI4CE PINN 94 50 0 26 May 2019
End-to-End Learned Random Walker for Seeded Image Segmentation Lorenzo Cerrone Alexander Zeilmann Fred Hamprecht 73 20 0 22 May 2019
Least Squares Auto-Tuning Shane T. Barratt Stephen P. Boyd MoMe 82 23 0 10 Apr 2019
Meta-Learning with Differentiable Convex Optimization Kwonjoon Lee Subhransu Maji Avinash Ravichandran Stefano Soatto 124 1,271 0 07 Apr 2019
Controlling Neural Networks via Energy Dissipation Michael Möller Thomas Möllenhoff Zorah Lähner 70 17 0 05 Apr 2019
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games Chun Kai Ling Fei Fang J. Zico Kolter 83 29 0 11 Mar 2019
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data Gabriel Loaiza-Ganem Sean M. Perkins Karen E. Schroeder Mark M. Churchland John P. Cunningham 3DPC 94 14 0 06 Mar 2019
End-to-End Game-Focused Learning of Adversary Behavior in Security Games Andrew Perrault Bryan Wilder Eric Ewing Aditya Mate B. Dilkina Milind Tambe AAML 408 10 0 03 Mar 2019
Introspection Learning Chris R. Serrano Michael A. Warren 41 0 0 27 Feb 2019
A Differentiable Augmented Lagrangian Method for Bilevel Nonlinear Optimization Benoit Landry Zachary Manchester Marco Pavone 92 20 0 08 Feb 2019
Tensor Variable Elimination for Plated Factor Graphs F. Obermeyer Eli Bingham M. Jankowiak Justin T. Chiu Neeraj Pradhan Alexander M. Rush Noah D. Goodman 97 23 0 08 Feb 2019
Homogeneous Linear Inequality Constraints for Neural Network Activations Thomas Frerix Matthias Nießner Zorah Lähner 82 7 0 05 Feb 2019
End-to-end Lane Detection through Differentiable Least-Squares Fitting Wouter Van Gansbeke Bert De Brabandere D. Neven Marc Proesmans Luc Van Gool 82 136 0 01 Feb 2019
Lyapunov-based Safe Policy Optimization for Continuous Control Yinlam Chow Ofir Nachum Aleksandra Faust Edgar A. Duénez-Guzmán Mohammad Ghavamzadeh 108 247 0 28 Jan 2019
End-to-end Learning for Graph Decomposition Mingli Song Bjoern Andres Michael J. Black Otmar Hilliges Siyu Tang 47 16 0 23 Dec 2018