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Type prediction

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보존된 평가 기록

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코드

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

https://github.com/BeautyOfWeb/AffinityNet

공식 코드

AffinityNet: semi-supervised few-shot learning for disease type prediction

https://github.com/RiyasaatAhmed/Text2Chart-A-Multi-Staged-Chart-Generator-from-Natural-Language-Text

공식 코드

Text2Chart: A Multi-Staged Chart Generator from Natural Language Text

https://github.com/SkBlaz/tax2vec

공식 코드

tax2vec: Constructing Interpretable Features from Taxonomies for Short Text Classification

https://github.com/alan-turing-institute/SemAIDA

공식 코드

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

https://github.com/alejgh/wikidata-edithist-refinement

공식 코드

Leveraging Wikidata's edit history in knowledge graph refinement tasks

https://github.com/atrautsch/nlbse2022_replication_kit

공식 코드

Predicting Issue Types with seBERT

https://github.com/biasvariancelabs/aitlas

공식 코드

AiTLAS: Artificial Intelligence Toolbox for Earth Observation

https://github.com/chenlabgccri/CancerTypePrediction

공식 코드

Convolutional neural network models for cancer type prediction based on gene expression

https://github.com/computationalpathologygroup/hooknet

공식 코드

HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images

https://github.com/cooelf/Auto-UI

공식 코드

You Only Look at Screens: Multimodal Chain-of-Action Agents

https://github.com/cooelf/auto-gui

공식 코드

You Only Look at Screens: Multimodal Chain-of-Action Agents

https://github.com/danaesavi/poi-type-prediction

공식 코드

Point-of-Interest Type Prediction using Text and Images

https://github.com/dice-group/PYKE

공식 코드

A Physical Embedding Model for Knowledge Graphs

https://github.com/futianfan/mimosa

공식 코드

MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization

https://github.com/gammatauai/opentau

공식 코드

Type Prediction With Program Decomposition and Fill-in-the-Type Training

https://github.com/glycanml/glycanml

공식 코드

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning

https://github.com/google-research/bert

공식 코드

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/jeffhao-alboran/Bio-JOIE

공식 코드

Bio-JOIE: Joint Representation Learning of Biological Knowledge Bases

https://github.com/joernio/joernti-codetidal5

공식 코드

Learning Type Inference for Enhanced Dataflow Analysis

https://github.com/karlstratos/mention2vec

공식 코드

Entity Identification as Multitasking

https://github.com/kennthshang/phatyp

공식 코드

PhaTYP: Predicting the lifestyle for bacteriophages using BERT

https://github.com/liyuechao1998/scgsl

공식 코드

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data

https://github.com/megagonlabs/doduo

공식 코드

Annotating Columns with Pre-trained Language Models

https://github.com/microsoft/CodeBERT

공식 코드

CodeBERT: A Pre-Trained Model for Programming and Natural Languages

https://github.com/modelscope/adaseq

공식 코드

Recall, Expand and Multi-Candidate Cross-Encode: Fast and Accurate Ultra-Fine Entity Typing

https://github.com/parasj/contracode

공식 코드

Contrastive Code Representation Learning

https://github.com/pytorch/fairseq

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RoBERTa: A Robustly Optimized BERT Pretraining Approach

https://github.com/rajathpatel23/joint-kge-fnet-lm

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On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling

https://github.com/regenkordel/lynx-beyondduplicates

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Beyond Duplicates: Towards Understanding and Predicting Link Types in Issue Tracking Systems

https://github.com/saltudelft/type4py

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Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python

https://github.com/smart-task/smart-dataset

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SeMantic AnsweR Type prediction task (SMART) at ISWC 2020 Semantic Web Challenge

https://github.com/svjan5/medtype

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Improving Broad-Coverage Medical Entity Linking with Semantic Type Prediction and Large-Scale Datasets

https://github.com/utopia-group/typet5

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TypeT5: Seq2seq Type Inference using Static Analysis

https://github.com/xbmxb/aagent

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CoCo-Agent: A Comprehensive Cognitive MLLM Agent for Smartphone GUI Automation

https://github.com/xbmxb/coco-agent

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CoCo-Agent: A Comprehensive Cognitive MLLM Agent for Smartphone GUI Automation

https://github.com/yuqiu-rgb/uniptms

공식 코드

UniPTMs: The First Unified Multi-type PTM Site Prediction Model via Master-Slave Architecture-Based Multi-Stage Fusion Strategy and Hierarchical Contrastive Loss

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.