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 601610 of 639 papers

TitleStatusHype
Supervised Neural Clustering via Latent Structured Output Learning: Application to Question IntentsCode0
Unsupervised Neural Dependency ParsingCode0
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot ModelsCode0
Semi-supervised Structured Prediction with Neural CRF AutoencoderCode0
Coalescing Global and Local Information for Procedural Text UnderstandingCode0
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on GraphsCode0
Memory Augmented Policy Optimization for Program Synthesis and Semantic ParsingCode0
Convolutional Pose MachinesCode0
Convolutional Color ConstancyCode0
CF-OPT: Counterfactual Explanations for Structured PredictionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified