SOTAVerified

Structured Prediction

Structured Prediction is an area of machine learning focusing on representations of spaces with combinatorial structure, and algorithms for inference and parameter estimation over these structures. Core methods include both tractable exact approaches like dynamic programming and spanning tree algorithms as well as heuristic techniques such as linear programming relaxations and greedy search.

Source: Torch-Struct: Deep Structured Prediction Library

Papers

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Showing 311–320 of 639 papers

TitleStatusHype
Distilling Knowledge for Search-based Structured PredictionCode0
Adversarial Constraint Learning for Structured PredictionCode0
Complex Relations in a Deep Structured Prediction Model for Fine Image Segmentation—0
Learning latent variable structured prediction models with Gaussian perturbations—0
Generative Code Modeling with GraphsCode0
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time—0
Adversarial Structure Matching for Structured Prediction TasksCode0
Portuguese Named Entity Recognition using Conditional Random Fields and Local Grammars—0
Fast View Synthesis with Deep Stereo Vision—0
Online Non-Additive Path Learning under Full and Partial Information—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified