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Structured Prediction

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/lcalem/diva

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Diverse Probabilistic Trajectory Forecasting with Admissibility Constraints

https://github.com/leafmonkeylabs/semantix

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Meaning Typed Prompting: A Technique for Efficient, Reliable Structured Output Generation

https://github.com/lisha-chen/Deep-structured-facial-landmark-detection

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Deep Structured Prediction for Facial Landmark Detection

https://github.com/liujch1998/SoftLabelCCRF

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Phrase Grounding by Soft-Label Chain Conditional Random Field

https://github.com/locuslab/icnn

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Input Convex Neural Networks

https://github.com/lpmp/bdd

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FastDOG: Fast Discrete Optimization on GPU

https://github.com/lyutyuh/asp

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Autoregressive Structured Prediction with Language Models

https://github.com/mainlp/logme-nlp

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Evidence > Intuition: Transferability Estimation for Encoder Selection

https://github.com/maria-korosteleva/Garment-Pattern-Estimation

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NeuralTailor: Reconstructing Sewing Pattern Structures from 3D Point Clouds of Garments

https://github.com/mattbierbaum/arxiv-public-datasets

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On the Use of ArXiv as a Dataset

https://github.com/mayer123/cgli

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Coalescing Global and Local Information for Procedural Text Understanding

https://github.com/mblondel/projection-losses

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Structured Prediction with Projection Oracles

https://github.com/megagonlabs/sato

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Sato: Contextual Semantic Type Detection in Tables

https://github.com/microsoft/reliableai

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Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning

https://github.com/mods333/energy-based-scene-graph

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Energy-Based Learning for Scene Graph Generation

https://github.com/mohsenzand/motionflow

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Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics

https://github.com/namisan/mt-dnn

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The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding

https://github.com/negrinho/beam_learn_supertagging

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An Empirical Investigation of Beam-Aware Training in Supertagging

https://github.com/orlitany/DeepFunctionalMaps

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Deep Functional Maps: Structured Prediction for Dense Shape Correspondence

https://github.com/person594/regccrf-experiments

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Constraining Linear-chain CRFs to Regular Languages

https://github.com/pluslabnlp/clap

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Contextual Label Projection for Cross-Lingual Structured Prediction

https://github.com/pluslabnlp/degree

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DEGREE: A Data-Efficient Generation-Based Event Extraction Model

https://github.com/princeton-nlp/PURE

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A Frustratingly Easy Approach for Entity and Relation Extraction

https://github.com/psunlpgroup/fish-dip

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Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning

https://github.com/pytorch/fairseq

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Classical Structured Prediction Losses for Sequence to Sequence Learning

https://github.com/rksltnl/Deep-Metric-Learning-CVPR16

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Deep Metric Learning via Lifted Structured Feature Embedding

https://github.com/shavarani/spel

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SpEL: Structured Prediction for Entity Linking

https://github.com/shikorab/SceneGraph

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Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction

https://github.com/siddharthachandra/gcrf

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Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs

https://github.com/speedcell4/parserker

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To be Continuous, or to be Discrete, Those are Bits of Questions

https://github.com/sprocketlab/ws-structured-prediction

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Lifting Weak Supervision To Structured Prediction

https://github.com/sustcsonglin/pointer-net-for-nested

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Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer Networks

https://github.com/swiseman/neighbor-tagging

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Label-Agnostic Sequence Labeling by Copying Nearest Neighbors

https://github.com/tamim-el/dsokr

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Deep Sketched Output Kernel Regression for Structured Prediction

https://github.com/tamim-el/sisokr

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Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels

https://github.com/tensorflow/tensor2tensor

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On the Discrepancy between Density Estimation and Sequence Generation

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