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 511520 of 639 papers

TitleStatusHype
Learning Constrained Structured Spaces with Application to Multi-Graph MatchingCode0
Detect, Replace, Refine: Deep Structured Prediction For Pixel Wise LabelingCode0
Learning Constraints for Structured Prediction Using Rectifier NetworksCode0
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak SupervisionCode0
Dr.VOT : Measuring Positive and Negative Voice Onset Time in the WildCode0
Bandit Structured Prediction for Neural Sequence-to-Sequence LearningCode0
Adversarial Structure Matching for Structured Prediction TasksCode0
Adversarial Constraint Learning for Structured PredictionCode0
Reasoning about Actions and State Changes by Injecting Commonsense KnowledgeCode0
Reciprocal Supervised Learning Improves Neural Machine TranslationCode0
Show:102550
← PrevPage 52 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified