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Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

8 August 2022

Papers citing "Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions"

50 / 51 papers shown

Title
Graph Neural Networks are Dynamic Programmers Andrew Dudzik Petar Velickovic 89 64 0 29 Mar 2022
Submodularity In Machine Learning and Artificial Intelligence J. Bilmes 52 57 0 31 Jan 2022
Neural Algorithmic Reasoners are Implicit Planners Andreea Deac Petar Velivcković Ognjen Milinković Pierre-Luc Bacon Jian Tang Mladen Nikolic OffRL 64 23 0 11 Oct 2021
Combinatorial Optimization with Physics-Inspired Graph Neural Networks M. Schuetz J. K. Brubaker H. Katzgraber AI4CE 80 185 0 02 Jul 2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions Mathias Niepert Pasquale Minervini Luca Franceschi 62 85 0 03 Jun 2021
Neural Algorithmic Reasoning Petar Velickovic Charles Blundell NAI OOD 44 104 0 06 May 2021
CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints Anselm Paulus Michal Rolínek Vít Musil Brandon Amos Georg Martius 43 61 0 05 May 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 79 358 0 18 Feb 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 343 1,928 0 12 Nov 2020
Complex Query Answering with Neural Link Predictors Erik Arakelyan Daniel Daza Pasquale Minervini Michael Cochez 71 134 0 06 Nov 2020
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator Max B. Paulus Chris J. Maddison Andreas Krause BDL 67 42 0 09 Oct 2020
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 236 821 0 16 Jul 2020
Strong Generalization and Efficiency in Neural Programs Yujia Li Felix Gimeno Pushmeet Kohli Oriol Vinyals 109 17 0 07 Jul 2020
Neural Execution Engines: Learning to Execute Subroutines Yujun Yan Kevin Swersky Danai Koutra Parthasarathy Ranganathan Milad Hashemi NAI 59 42 0 15 Jun 2020
Gradient Estimation with Stochastic Softmax Tricks Max B. Paulus Dami Choi Daniel Tarlow Andreas Krause Chris J. Maddison BDL 76 88 0 15 Jun 2020
Reinforcement Learning for Combinatorial Optimization: A Survey Nina Mazyavkina S. Sviridov Sergei Ivanov Evgeny Burnaev 107 624 0 07 Mar 2020
Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings Hongyu Ren Weihua Hu J. Leskovec 56 309 0 14 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 375 18,778 0 13 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 520 42,559 0 03 Dec 2019
Differentiable Convex Optimization Layers Akshay Agrawal Brandon Amos Shane T. Barratt Stephen P. Boyd Steven Diamond Zico Kolter 88 663 0 28 Oct 2019
Neural Execution of Graph Algorithms Petar Velickovic Rex Ying Matilde Padovano R. Hadsell Charles Blundell GNN 85 169 0 23 Oct 2019
Graph Neural Networks for Maximum Constraint Satisfaction Jan Toenshoff Martin Ritzert Hinrikus Wolf Martin Grohe GNN NAI AI4CE 48 60 0 18 Sep 2019
Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods Ching-An Cheng Xinyan Yan Byron Boots 57 22 0 08 Aug 2019
What Can Neural Networks Reason About? Keyulu Xu Jingling Li Mozhi Zhang S. Du Ken-ichi Kawarabayashi Stefanie Jegelka NAI AI4CE 73 246 0 30 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 78 265 0 29 May 2019
Optimal approximation for unconstrained non-submodular minimization Marwa El Halabi Stefanie Jegelka 41 25 0 29 May 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 229 4,341 0 06 Mar 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 240 1,655 0 28 Dec 2018
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon Yoshua Bengio Andrea Lodi Antoine Prouvost 155 1,391 0 15 Nov 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 224 1,275 0 04 Oct 2018
Embedding Logical Queries on Knowledge Graphs William L. Hamilton Payal Bajaj Marinka Zitnik Dan Jurafsky J. Leskovec NAI 82 290 0 05 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 764 3,129 0 04 Jun 2018
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines Cathy Wu Aravind Rajeswaran Yan Duan Vikash Kumar Alexandre M. Bayen Sham Kakade Igor Mordatch Pieter Abbeel OffRL 63 153 0 20 Mar 2018
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation Will Grathwohl Dami Choi Yuhuai Wu Geoffrey Roeder David Duvenaud 99 300 0 31 Oct 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,225 0 30 Oct 2017
Combinatorial Penalties: Which structures are preserved by convex relaxations? Marwa El Halabi Francis R. Bach Volkan Cevher 62 16 0 17 Oct 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 725 132,199 0 12 Jun 2017
OptNet: Differentiable Optimization as a Layer in Neural Networks Brandon Amos J. Zico Kolter 163 971 0 01 Mar 2017
Neural Combinatorial Optimization with Reinforcement Learning Irwan Bello Hieu H. Pham Quoc V. Le Mohammad Norouzi Samy Bengio 158 1,492 0 29 Nov 2016
Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic S. Gu Timothy Lillicrap Zoubin Ghahramani Richard Turner Sergey Levine OffRL BDL 88 345 0 07 Nov 2016
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 344 5,372 0 03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 196 2,538 0 02 Nov 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 276 11,151 0 14 Mar 2016
Gated Graph Sequence Neural Networks Yujia Li Daniel Tarlow Marc Brockschmidt R. Zemel GNN 347 3,285 0 17 Nov 2015
Submodular Functions: from Discrete to Continous Domains Francis R. Bach 125 149 0 02 Nov 2015
On the tightness of an SDP relaxation of k-means Takayuki Iguchi D. Mixon Jesse Peterson Soledad Villar 94 33 0 18 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.9K 150,260 0 22 Dec 2014
A useful variant of the Davis--Kahan theorem for statisticians Yi Yu Tengyao Wang R. Samworth 98 579 0 04 May 2014
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 384 3,151 0 15 Aug 2013
Theano: new features and speed improvements Frédéric Bastien Pascal Lamblin Razvan Pascanu James Bergstra Ian Goodfellow Arnaud Bergeron Nicolas Bouchard David Warde-Farley Yoshua Bengio 94 1,420 0 23 Nov 2012