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 221–230 of 639 papers

TitleStatusHype
Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction—0
Capturing Dialogue State Variable Dependencies with an Energy-based Neural Dialogue State Tracker—0
Phrase Grounding by Soft-Label Chain Conditional Random FieldCode0
Learning Rich Representations For Structured Visual Prediction Tasks—0
Increasing the Generalisation Capacity of Conditional VAEs—0
UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task DistillationCode0
Learning the Relation between Code Features and Code Transforms with Structured PredictionCode0
An Embedding Framework for Consistent Polyhedral Surrogates—0
Unsupervised Cross-Lingual Representation Learning—0
Approximate Inference in Structured Instances with Noisy Categorical Observations—0
Show:102550
← PrevPage 23 of 64Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified