SparseMAP: Differentiable Sparse Structured Inference

12 February 2018

André F. T. Martins

Papers citing "SparseMAP: Differentiable Sparse Structured Inference"

21 / 21 papers shown

Title
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers Anselm Paulus Georg Martius Vít Musil AI4CE 55 1 0 08 Jul 2024
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 35 1 0 14 Aug 2023
Efficient Learning of Discrete-Continuous Computation Graphs David Friede Mathias Niepert 13 3 0 26 Jul 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 29 11 0 27 Jan 2023
SIMPLE: A Gradient Estimator for $k$ -Subset Sampling Kareem Ahmed Zhe Zeng Mathias Niepert Mathias Niepert BDL 48 25 0 04 Oct 2022
Contrasting quadratic assignments for set-based representation learning A. Moskalev Ivan Sosnovik Volker Fischer A. Smeulders SSL 32 9 0 31 May 2022
Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies Alon Berliner Guy Rotman Yossi Adi Roi Reichart Tamir Hazan BDL DRL 26 4 0 03 May 2022
Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Phil Chen Masha Itkina Ransalu Senanayake Mykel J. Kochenderfer 41 6 0 27 Oct 2021
Sinkformers: Transformers with Doubly Stochastic Attention Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 32 77 0 22 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 28 94 0 04 Oct 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 72 369 0 01 Sep 2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions Mathias Niepert Pasquale Minervini Luca Franceschi 32 81 0 03 Jun 2021
Storchastic: A Framework for General Stochastic Automatic Differentiation Emile van Krieken Jakub M. Tomczak A. T. Teije ODL OffRL 31 15 0 01 Apr 2021
Gradient Estimation with Stochastic Softmax Tricks Max B. Paulus Dami Choi Daniel Tarlow Andreas Krause Chris J. Maddison BDL 38 85 0 15 Jun 2020
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport Kyle Swanson L. Yu Tao Lei OT 29 37 0 27 May 2020
Learning with Differentiable Perturbed Optimizers Quentin Berthet Mathieu Blondel O. Teboul Marco Cuturi Jean-Philippe Vert Francis R. Bach 29 106 0 20 Feb 2020
Graph Structured Prediction Energy Networks Colin Graber Alex Schwing 21 17 0 31 Oct 2019
Structured Prediction with Projection Oracles Mathieu Blondel 21 33 0 24 Oct 2019
The Limited Multi-Label Projection Layer Brandon Amos V. Koltun J. Zico Kolter 29 36 0 20 Jun 2019
Augmenting Neural Networks with First-order Logic Tao Li Vivek Srikumar 16 109 0 14 Jun 2019
Sparse Sequence-to-Sequence Models Ben Peters Vlad Niculae André F. T. Martins TPM 27 209 0 14 May 2019