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
CrossBeam: Learning to Search in Bottom-Up Program SynthesisCode1
SPEECH: Structured Prediction with Energy-Based Event-Centric HyperspheresCode1
StructPool: Structured Graph Pooling via Conditional Random FieldsCode1
Structured Multi-task Learning for Molecular Property PredictionCode1
Deep Structured Prediction with Nonlinear Output TransformationsCode0
A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on GraphsCode0
Dense and Low-Rank Gaussian CRFs Using Deep EmbeddingsCode0
Deep Metric Learning via Lifted Structured Feature EmbeddingCode0
A Probabilistic Generative Grammar for Semantic ParsingCode0
Deep Sketched Output Kernel Regression for Structured PredictionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8Unverified