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 251–260 of 639 papers

TitleStatusHype
Deep imitation learning for molecular inverse problems—0
Hierarchical Poset Decoding for Compositional Generalization in Language—0
Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction—0
Houdini: Fooling Deep Structured Prediction Models—0
A Structured Prediction Approach for Missing Value Imputation—0
A Joint Sequential and Relational Model for Frame-Semantic Parsing—0
A Discriminative Graph-Based Parser for the Abstract Meaning Representation—0
Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training—0
Exact inference in structured prediction—0
Cross-Lingual Discriminative Learning of Sequence Models with Posterior Regularization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified