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 301–350 of 639 papers

TitleStatusHype
Direct Shape Regression Networks for End-to-End Face Alignment—0
HCCL at SemEval-2018 Task 8: An End-to-End System for Sequence Labeling from Cybersecurity Reports—0
Training Structured Prediction Energy Networks with Indirect Supervision—0
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical ModelsCode0
Distilling Knowledge for Search-based Structured PredictionCode0
Adversarial Constraint Learning for Structured PredictionCode0
Complex Relations in a Deep Structured Prediction Model for Fine Image Segmentation—0
Learning latent variable structured prediction models with Gaussian perturbations—0
Generative Code Modeling with GraphsCode0
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time—0
Adversarial Structure Matching for Structured Prediction TasksCode0
Portuguese Named Entity Recognition using Conditional Random Fields and Local Grammars—0
Fast View Synthesis with Deep Stereo Vision—0
Online Non-Additive Path Learning under Full and Partial Information—0
Learning Approximate Inference Networks for Structured PredictionCode1
Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired DataCode0
Mapping Images to Scene Graphs with Permutation-Invariant Structured PredictionCode0
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction—0
SparseMAP: Differentiable Sparse Structured InferenceCode0
Differentiable Dynamic Programming for Structured Prediction and Attention—0
Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural NetworkCode0
Deep Structured Energy-Based Image InpaintingCode0
Multi-Task Spatiotemporal Neural Networks for Structured Surface ReconstructionCode0
Residual Loss Prediction: Reinforcement Learning With No Incremental FeedbackCode0
Adversarial Structured Prediction for Multivariate Measures—0
Structured Set Matching Networks for One-Shot Part Labeling—0
A Learning Error Analysis for Structured Prediction with Approximate Inference—0
On the Robustness of Semantic Segmentation Models to Adversarial AttacksCode0
Complex Structure Leads to Overfitting: A Structure Regularization Decoding Method for Natural Language Processing—0
Dialogue Act Recognition via CRF-Attentive Structured Network—0
Classical Structured Prediction Losses for Sequence to Sequence Learning—0
Document Context Neural Machine Translation with Memory Networks—0
Optimality of Approximate Inference Algorithms on Stable Instances—0
Deep Learning in Lexical Analysis and Parsing—0
Dense and Low-Rank Gaussian CRFs Using Deep EmbeddingsCode0
Active Learning amidst Logical KnowledgeCode0
Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic MapsCode0
Optimizing for Measure of Performance in Max-Margin Parsing—0
A Unified Framework for Structured Prediction: From Theory to Practice—0
Structured Prediction via Learning to Search under Bandit Feedback—0
Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing—0
Syntax Aware LSTM model for Semantic Role Labeling—0
Spatial Language Understanding with Multimodal Graphs using Declarative Learning based Programming—0
Boosting Information Extraction Systems with Character-level Neural Networks and Free Noisy Supervision—0
A Joint Sequential and Relational Model for Frame-Semantic Parsing—0
Semi-supervised Structured Prediction with Neural CRF AutoencoderCode0
End-to-End Neural Relation Extraction with Global Optimization—0
Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation—0
Robust Conditional Probabilities—0
Parametric Adversarial Divergences are Good Losses for Generative Modeling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CVAENegative CLL71.8—Unverified