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 5160 of 639 papers

TitleStatusHype
SpEL: Structured Prediction for Entity LinkingCode1
StructPool: Structured Graph Pooling via Conditional Random FieldsCode1
CrossBeam: Learning to Search in Bottom-Up Program SynthesisCode1
Structured Output Learning with Conditional Generative FlowsCode1
Diverse Probabilistic Trajectory Forecasting with Admissibility ConstraintsCode0
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on GraphsCode0
Distilling Knowledge for Search-based Structured PredictionCode0
Deep Structured Prediction with Nonlinear Output TransformationsCode0
A Probabilistic Generative Grammar for Semantic ParsingCode0
Dense and Low-Rank Gaussian CRFs Using Deep EmbeddingsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified