Implicit MLE: Backpropagating Through Discrete Exponential Family
Distributions

Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions

3 June 2021

Mathias Niepert

Pasquale Minervini

Luca Franceschi

Papers citing "Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions"

19 / 19 papers shown

Title
A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning Amadou S. Sangare Nicolas Dunou Jhony H. Giraldo Fragkiskos D. Malliaros SSL 64 0 0 28 Feb 2025
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers Anselm Paulus Georg Martius Vít Musil AI4CE 49 1 0 08 Jul 2024
Learning Latent Graph Structures and their Uncertainty A. Manenti Daniele Zambon Cesare Alippi BDL 38 1 0 30 May 2024
SynJax: Structured Probability Distributions for JAX Miloš Stanojević Laurent Sartran SyDa 13 4 0 07 Aug 2023
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities Jayanta Mandi James Kotary Senne Berden Maxime Mulamba Víctor Bucarey Tias Guns Ferdinando Fioretto AI4CE 28 55 0 25 Jul 2023
Differentiable Random Partition Models Thomas M. Sutter Alain Ryser Joram Liebeskind Julia E. Vogt 42 3 0 26 May 2023
From Relational Pooling to Subgraph GNNs: A Universal Framework for More Expressive Graph Neural Networks Cai Zhou Xiyuan Wang Muhan Zhang 35 14 0 08 May 2023
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks Indro Spinelli Riccardo Bianchini Simone Scardapane 26 1 0 22 Feb 2023
Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective Michael E. Sander J. Puigcerver Josip Djolonga Gabriel Peyré Mathieu Blondel 21 18 0 02 Feb 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 27 11 0 27 Jan 2023
A Solver-Free Framework for Scalable Learning in Neural ILP Architectures Yatin Nandwani Rishabh Ranjan Mausam Parag Singla 33 7 0 17 Oct 2022
SIMPLE: A Gradient Estimator for $k$ -Subset Sampling Kareem Ahmed Zhe Zeng Mathias Niepert Guy Van den Broeck BDL 45 24 0 04 Oct 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 33 7 0 28 Sep 2022
Theseus: A Library for Differentiable Nonlinear Optimization Luis Pineda Taosha Fan Maurizio Monge S. Venkataraman Paloma Sodhi ... Austin S. Wang Stuart Anderson Jing Dong Brandon Amos Mustafa Mukadam 26 76 0 19 Jul 2022
On Quantum Circuits for Discrete Graphical Models Nico Piatkowski Christa Zoufal 19 4 0 01 Jun 2022
Sparse Graph Learning from Spatiotemporal Time Series Andrea Cini Daniele Zambon Cesare Alippi CML AI4TS 43 18 0 26 May 2022
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 347 0 18 Feb 2021
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 110 716 0 13 Jun 2018
Learning Attitudes and Attributes from Multi-Aspect Reviews Julian McAuley J. Leskovec Dan Jurafsky 200 296 0 15 Oct 2012