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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Alibaba-NLP/ACE
공식 코드Automated Concatenation of Embeddings for Structured Prediction
https://github.com/Alibaba-NLP/StructuralKD
공식 코드Structural Knowledge Distillation: Tractably Distilling Information for Structured Predictor
https://github.com/CMU-Perceptual-Computing-Lab/convolutional-pose-machines-release
공식 코드https://github.com/CZWin32768/XLM-Align
공식 코드Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment
https://github.com/GermainVivierArdisson/CF-OPT
공식 코드CF-OPT: Counterfactual Explanations for Structured Prediction
https://github.com/HeddaCohenIndelman/PerturbedStructuredPredictorsDirect
공식 코드Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization
https://github.com/Linwenye/Efficient-KD
공식 코드https://github.com/Lixy1997/Group-WSSS
공식 코드Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation
https://github.com/MLSpeech/Dr.VOT
공식 코드Dr.VOT : Measuring Positive and Negative Voice Onset Time in the Wild
https://github.com/Microsoft/graph-based-code-modelling
공식 코드https://github.com/MinkaiXu/RSL-NMT
공식 코드Reciprocal Supervised Learning Improves Neural Machine Translation
https://github.com/Oneplus/twpipe
공식 코드https://github.com/PAIR-code/lit
공식 코드https://github.com/QData/JEEK
공식 코드https://github.com/QData/JointNets
공식 코드Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge
https://github.com/RemiLeblond/SeaRNN-open
공식 코드https://github.com/RuohanW/Tasml
공식 코드https://github.com/TorchCraft/TorchCraftAI
공식 코드https://github.com/VivienCabannes/infimum_loss
공식 코드Structured Prediction with Partial Labelling through the Infimum Loss
https://github.com/VivienCabannes/partial_labelling
공식 코드Structured Prediction with Partial Labelling through the Infimum Loss
https://github.com/WinnieHAN/structure_adv
공식 코드Adversarial Attack and Defense of Structured Prediction Models
https://github.com/XiaoxiaoGuo/rcdqn
공식 코드https://github.com/Yaakoubi/Struct-CKN
공식 코드Structured Convolutional Kernel Networks for Airline Crew Scheduling
https://github.com/ZubinGou/multi-view-prompting
공식 코드MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
https://github.com/abhyudaynj/LSTM-CRF-models
공식 코드Structured prediction models for RNN based sequence labeling in clinical text
https://github.com/adamkhakhar/python-pac-code-prediction-set
공식 코드https://github.com/adiyoss/AutoVowelDuration
공식 코드Automatic measurement of vowel duration via structured prediction
https://github.com/akorba/Structured_Approach_Label_Ranking
공식 코드https://github.com/alexnowakvila/maxminloss
공식 코드Consistent Structured Prediction with Max-Min Margin Markov Networks
https://github.com/alirezamshi/G2GTr
공식 코드Graph-to-Graph Transformer for Transition-based Dependency Parsing
https://github.com/allenai/interscript
공식 코드Interscript: A dataset for interactive learning of scripts through error feedback
https://github.com/allenai/propara
공식 코드Reasoning about Actions and State Changes by Injecting Commonsense Knowledge
https://github.com/amazon-research/tanl
공식 코드Structured Prediction as Translation between Augmented Natural Languages
https://github.com/aosokin/consistentSurrogates_derivations
공식 코드On Structured Prediction Theory with Calibrated Convex Surrogate Losses
https://github.com/arthurdevnl/lazyk
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.