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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 121–130 of 639 papers

TitleStatusHype
Supervised Neural Clustering via Latent Structured Output Learning: Application to Question IntentsCode0
On the Consistency of Max-Margin Losses—0
Structured Convolutional Kernel Networks for Airline Crew SchedulingCode0
Flow-based Spatio-Temporal Structured Prediction of Motion DynamicsCode0
Neuro-Symbolic Constraint Programming for Structured Prediction—0
Set-to-Sequence Methods in Machine Learning: a Review—0
Energy-Based Learning for Scene Graph GenerationCode1
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot ModelsCode0
On the Fundamental Limits of Exact Inference in Structured Prediction—0
Unifying Lower Bounds on Prediction Dimension of Consistent Convex Surrogates—0
Show:102550
← PrevPage 13 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified