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

Showing 8190 of 639 papers

TitleStatusHype
Bandit Structured Prediction for Neural Sequence-to-Sequence LearningCode0
An Empirical Investigation of Beam-Aware Training in SupertaggingCode0
Distilling Knowledge for Search-based Structured PredictionCode0
Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural NetworkCode0
Adversarial Structure Matching for Structured Prediction TasksCode0
Bayesian Structured Prediction Using Gaussian ProcessesCode0
Dense and Low-Rank Gaussian CRFs Using Deep EmbeddingsCode0
Benchmarking Approximate Inference Methods for Neural Structured PredictionCode0
Automatic measurement of vowel duration via structured predictionCode0
Deep Structured Prediction with Nonlinear Output TransformationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified