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 501–510 of 639 papers

TitleStatusHype
Pre- and In-Parsing Models for Neural Empty Category Detection—0
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction—0
Predicting deliberative outcomes—0
Predicting deliberative outcomes—0
Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP—0
Distilling Knowledge for Search-based Structured PredictionCode0
Learning Beam Search Policies via Imitation LearningCode0
Slack and Margin Rescaling as Convex Extensions of Supermodular FunctionsCode0
Bayesian Structured Prediction Using Gaussian ProcessesCode0
Diverse Probabilistic Trajectory Forecasting with Admissibility ConstraintsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified