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 501–550 of 639 papers

TitleStatusHype
Pre- and In-Parsing Models for Neural Empty Category Detection—0
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction—0
Predicting deliberative outcomes—0
Predicting deliberative outcomes—0
Predicting Structures in NLP: Constrained Conditional Models and Integer Linear Programming in NLP—0
Distilling Knowledge for Search-based Structured PredictionCode0
Learning Beam Search Policies via Imitation LearningCode0
Slack and Margin Rescaling as Convex Extensions of Supermodular FunctionsCode0
Bayesian Structured Prediction Using Gaussian ProcessesCode0
Diverse Probabilistic Trajectory Forecasting with Admissibility ConstraintsCode0
Learning Constrained Structured Spaces with Application to Multi-Graph MatchingCode0
Detect, Replace, Refine: Deep Structured Prediction For Pixel Wise LabelingCode0
Learning Constraints for Structured Prediction Using Rectifier NetworksCode0
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak SupervisionCode0
Dr.VOT : Measuring Positive and Negative Voice Onset Time in the WildCode0
Bandit Structured Prediction for Neural Sequence-to-Sequence LearningCode0
Adversarial Structure Matching for Structured Prediction TasksCode0
Adversarial Constraint Learning for Structured PredictionCode0
Reasoning about Actions and State Changes by Injecting Commonsense KnowledgeCode0
Reciprocal Supervised Learning Improves Neural Machine TranslationCode0
Transition-Based Syntactic Linearization with Lookahead FeaturesCode0
Learning Fast-Mixing Models for Structured PredictionCode0
Reconstructing the house from the ad: Structured prediction on real estate classifiedsCode0
Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic MapsCode0
Learning Hierarchical Interactions at Scale: A Convex Optimization ApproachCode0
Conditional Random Field Autoencoders for Unsupervised Structured PredictionCode0
Efficient Structured Inference for Transition-Based Parsing with Neural Networks and Error StatesCode0
Reducing Model Churn: Stable Re-training of Conversational AgentsCode0
Efficient Sub-structured Knowledge DistillationCode0
SparseMAP: Differentiable Sparse Structured InferenceCode0
Dense and Low-Rank Gaussian CRFs Using Deep EmbeddingsCode0
End-to-End Instance Segmentation with Recurrent AttentionCode0
Learning Likelihoods with Conditional Normalizing FlowsCode0
The Concrete Distribution: A Continuous Relaxation of Discrete Random VariablesCode0
Deep Structured Prediction with Nonlinear Output TransformationsCode0
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss EmbeddingsCode0
Representation Learning for Text-level Discourse ParsingCode0
Structured Prediction with Projection OraclesCode0
ReSeg: A Recurrent Neural Network-based Model for Semantic SegmentationCode0
Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural NetworkCode0
Deep Structured Energy-Based Image InpaintingCode0
Residual Loss Prediction: Reinforcement Learning With No Incremental FeedbackCode0
Estimation from Indirect Supervision with Linear MomentsCode0
Deep Sketched Output Kernel Regression for Structured PredictionCode0
Evidence > Intuition: Transferability Estimation for Encoder SelectionCode0
Learning Randomly Perturbed Structured Predictors for Direct Loss MinimizationCode0
Experiment Segmentation in Scientific Discourse as Clause-level Structured Prediction using Recurrent Neural NetworksCode0
On Structured Prediction Theory with Calibrated Convex Surrogate LossesCode0
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired DataCode0
Learning Structured Output Representation using Deep Conditional Generative ModelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified