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"

50 / 583 papers shown

Title
On sensitivity of meta-learning to support data Mayank Agarwal Mikhail Yurochkin Yuekai Sun 100 21 0 26 Oct 2021
Integrated Conditional Estimation-Optimization Sirui Chen Paul Grigas Zuo‐Jun Max Shen CML 86 25 0 24 Oct 2021
Differentiable Rendering with Perturbed Optimizers Quentin Le Lidec Ivan Laptev Cordelia Schmid Justin Carpentier 76 15 0 18 Oct 2021
Abstract Interpretation of Fixpoint Iterators with Applications to Neural Networks Mark Niklas Muller Marc Fischer Robin Staab Martin Vechev 56 3 0 14 Oct 2021
Music Source Separation with Deep Equilibrium Models Yuichiro Koyama Naoki Murata Stefan Uhlich Giorgio Fabbro Shusuke Takahashi Yuki Mitsufuji 70 5 0 13 Oct 2021
Fast Approximations for Job Shop Scheduling: A Lagrangian Dual Deep Learning Method James Kotary Ferdinando Fioretto Pascal Van Hentenryck 100 20 0 12 Oct 2021
A global convergence theory for deep ReLU implicit networks via over-parameterization Tianxiang Gao Hailiang Liu Jia Liu Hridesh Rajan Hongyang Gao MLT 102 16 0 11 Oct 2021
Safe Reinforcement Learning Using Robust Control Barrier Functions Y. Emam Gennaro Notomista Paul Glotfelter Z. Kira M. Egerstedt OffRL 78 43 0 11 Oct 2021
A composable autoencoder-based iterative algorithm for accelerating numerical simulations Rishikesh Ranade C. Hill Haiyang He Amir Maleki Norman Chang Jay Pathak AI4CE 83 6 0 07 Oct 2021
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games Shinsaku Sakaue Kengo Nakamura 31 3 0 05 Oct 2021
Differentiable Spline Approximations Minsu Cho Aditya Balu Ameya Joshi Anjana Prasad Biswajit Khara Soumik Sarkar Baskar Ganapathysubramanian A. Krishnamurthy Chinmay Hegde 68 4 0 04 Oct 2021
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning Iris A. M. Huijben W. Kool Max B. Paulus Ruud J. G. van Sloun 115 99 0 04 Oct 2021
Implicit Riemannian Concave Potential Maps Danilo Jimenez Rezende S. Racanière AI4CE 98 7 0 04 Oct 2021
Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence Boyi Liu Jiayang Li Zhuoran Yang Hoi-To Wai Mingyi Hong Y. Nie Zhaoran Wang 146 20 0 04 Oct 2021
Lyapunov-stable neural-network control Hongkai Dai Benoit Landry Lujie Yang Marco Pavone Russ Tedrake 102 125 0 29 Sep 2021
DeepPSL: End-to-end perception and reasoning Sridhar Dasaratha Sai Akhil Puranam Karmvir Singh Phogat Sunil R. Tiyyagura Nigel P. Duffy BDL ReLM LRM 98 3 0 28 Sep 2021
Graph Neural Network-based Resource Allocation Strategies for Multi-Object Spectroscopy Tianshu Wang P. Melchior 91 7 0 27 Sep 2021
GPU Accelerated Batch Multi-Convex Trajectory Optimization for a Rectangular Holonomic Mobile Robot Fatemeh Rastgar Houman Masnavi Karl Kruusamäe A. Aabloo A. K. Singh 51 1 0 27 Sep 2021
Recursive Feasibility Guided Optimal Parameter Adaptation of Differential Convex Optimization Policies for Safety-Critical Systems Hardik Parwana Dimitra Panagou 66 19 0 22 Sep 2021
Is Attention Better Than Matrix Decomposition? Zhengyang Geng Meng-Hao Guo Hongxu Chen Xia Li Ke Wei Zhouchen Lin 125 142 0 09 Sep 2021
End-to-End Demand Response Model Identification and Baseline Estimation with Deep Learning Yuanyuan Shi Bolun Xu 30 1 0 02 Sep 2021
Implicit Behavioral Cloning Peter R. Florence Corey Lynch Andy Zeng Oscar Ramirez Ayzaan Wahid Laura Downs Adrian S. Wong Johnny Lee Igor Mordatch Jonathan Tompson OffRL 153 392 0 01 Sep 2021
Differentiable Moving Horizon Estimation for Robust Flight Control Bingheng Wang Zhengtian Ma Shupeng Lai Lin Zhao Tong-heng Lee 84 6 0 06 Aug 2021
LEO: Learning Energy-based Models in Factor Graph Optimization Paloma Sodhi Eric Dexheimer Mustafa Mukadam Stuart Anderson Michael Kaess 108 17 0 04 Aug 2021
Neural Fixed-Point Acceleration for Convex Optimization Shobha Venkataraman Brandon Amos 94 14 0 21 Jul 2021
Constrained Feedforward Neural Network Training via Reachability Analysis Long Kiu Chung Adam Dai Derek Knowles Shreyas Kousik Grace Gao 56 8 0 16 Jul 2021
An End-to-End Differentiable Framework for Contact-Aware Robot Design Jie Xu Tao Chen Lara Zlokapa Michael Foshey Wojciech Matusik Shinjiro Sueda Pulkit Agrawal 104 91 0 15 Jul 2021
Fast Contact-Implicit Model-Predictive Control Simon Le Cleac'h Taylor A. Howell Shuo Yang Chia-Yen Lee John Z. Zhang Arun L. Bishop Mac Schwager Zachary Manchester 191 85 0 12 Jul 2021
Learning structured approximations of combinatorial optimization problems Axel Parmentier TPM 24 4 0 09 Jul 2021
Stabilizing Equilibrium Models by Jacobian Regularization Shaojie Bai V. Koltun J. Zico Kolter 86 59 0 28 Jun 2021
DiffLoop: Tuning PID controllers by differentiating through the feedback loop Athindran Ramesh Kumar Peter J. Ramadge 78 13 0 19 Jun 2021
The Perils of Learning Before Optimizing Chris Cameron Jason S. Hartford Taylor Lundy Kevin Leyton-Brown 20 19 0 18 Jun 2021
Techniques for Symbol Grounding with SATNet Sever Topan David Rolnick X. Si NAI 98 23 0 16 Jun 2021
Learning Revenue-Maximizing Auctions With Differentiable Matching Michael J. Curry Uro Lyi Tom Goldstein John P. Dickerson 46 20 0 15 Jun 2021
Differentiable Robust LQR Layers Ngo Anh Vien Gerhard Neumann 54 4 0 10 Jun 2021
Nonsmooth Implicit Differentiation for Machine Learning and Optimization Jérôme Bolte Tam Le Edouard Pauwels Antonio Silveti-Falls 88 57 0 08 Jun 2021
Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning Kai Wang Sanket Shah Haipeng Chen Andrew Perrault Finale Doshi-Velez Milind Tambe OffRL 121 6 0 06 Jun 2021
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach Ahmed Abbas Paul Swoboda 66 14 0 06 Jun 2021
Learning Hard Optimization Problems: A Data Generation Perspective James Kotary Ferdinando Fioretto Pascal Van Hentenryck 54 38 0 04 Jun 2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions Mathias Niepert Pasquale Minervini Luca Franceschi 97 87 0 03 Jun 2021
Convergent Graph Solvers Junyoung Park J. Choo Jinkyoo Park 80 13 0 03 Jun 2021
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations Yingtao Luo Qiang Liu Yuntian Chen Wenbo Hu Tian Tian Jun Zhu DiffM 113 4 0 02 Jun 2021
Operator Splitting for Learning to Predict Equilibria in Convex Games Daniel McKenzie Howard Heaton Qiuwei Li Samy Wu Fung Stanley Osher Wotao Yin 78 0 0 02 Jun 2021
Large-Scale Wasserstein Gradient Flows Petr Mokrov Alexander Korotin Lingxiao Li Aude Genevay Justin Solomon Evgeny Burnaev 103 76 0 01 Jun 2021
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models Zaccharie Ramzi Florian Mannel Shaojie Bai Jean-Luc Starck P. Ciuciu Thomas Moreau 124 29 0 01 Jun 2021
Efficient and Modular Implicit Differentiation Mathieu Blondel Quentin Berthet Marco Cuturi Roy Frostig Stephan Hoyer Felipe Llinares-López Fabian Pedregosa Jean-Philippe Vert 126 238 0 31 May 2021
Safe Pontryagin Differentiable Programming Wanxin Jin Shaoshuai Mou George J. Pappas 99 41 0 31 May 2021
Optimization Induced Equilibrium Networks Xingyu Xie Qiuhao Wang Zenan Ling Xia Li Yisen Wang Guangcan Liu Zhouchen Lin 75 9 0 27 May 2021
Structural Causal Models Reveal Confounder Bias in Linear Program Modelling Matej Zečević Devendra Singh Dhami Kristian Kersting AAML 61 1 0 26 May 2021
Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization Bingqing Chen Neural Network Kyri Baker J. Zico Kolter Mario Berges 88 61 0 19 May 2021