Papers with Code 아카이브

Active Speaker Detection

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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/xinyiys/data_distribution_valuation

공식 코드

Data Distribution Valuation

https://github.com/xxhu94/csgnn

공식 코드

Cost Sensitive GNN-based Imbalanced Learning for Mobile Social Network Fraud Detection

https://github.com/xxhu94/gat-cobo

공식 코드

GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection

https://github.com/yushundong/edits

공식 코드

EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks

https://github.com/yzhao062/SUOD

공식 코드

SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection

https://github.com/yzhao062/pyod

공식 코드

PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection

https://github.com/yzhao062/pytod

공식 코드

TOD: GPU-accelerated Outlier Detection via Tensor Operations

https://github.com/zehong-wang/simmlp

공식 코드

SimMLP: Training MLPs on Graphs without Supervision

https://gitlab.com/Yvan_Lucas/hmm-ccfd

공식 코드

Multiple perspectives HMM-based feature engineering for credit card fraud detection

https://gitlab.com/lambda-hse/nfad

공식 코드

NFAD: Fixing anomaly detection using normalizing flows

https://github.com/Actis92/lit-saint

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

https://github.com/Actis92/saint-lightning

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

https://github.com/AniketP04/Credit-Card-Fraud-Detection

Credit Card Fraud Detection Using Autoencoder Neural Network

https://github.com/B-Deprez/NetworkFraud_BiRank_M2V_SAGE

https://github.com/Caspian-Ltd/Bayesian_stress_testing

Bayesian Stress Testing of Models in a Classification Hierarchy

https://github.com/DylanPerdigao/Bayesian-Optimization-1D-CSNN

https://github.com/DylanPerdigao/Neural-Joint-Activity-in-SNNs

https://github.com/HongleiXie/demo-CVAE

VOS: a Method for Variational Oversampling of Imbalanced Data

https://github.com/PonderLY/PC-GNN

https://github.com/Ryosaeba8/Anomaly_detection

Deep Anomaly Detection with Deviation Networks

https://github.com/XanaduAI/quantum-learning

Continuous-variable quantum neural networks

https://github.com/XanaduAI/quantum-neural-networks

Continuous-variable quantum neural networks

https://github.com/afourast/avobjects

Self-Supervised Learning of Audio-Visual Objects from Video

https://github.com/ajazturki10/Credit-Card-Fraud-Detection-using-Autoencoders

Credit Card Fraud Detection Using Autoencoder Neural Network

https://github.com/blackboxo/SplitGNN

https://github.com/depexo/BigDL-master

BigDL: A Distributed Deep Learning Framework for Big Data

https://github.com/dmlc/dgl/tree/master/examples/pytorch/caregnn

Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

https://github.com/doujiang-zheng/dynamic-preference-structure

APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding

https://github.com/dssg/aequitas

Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML Evaluation

https://github.com/dsulem/dynnet

Graph similarity learning for change-point detection in dynamic networks

https://github.com/feedzai/fairgbm

Promoting Fairness through Hyperparameter Optimization

https://github.com/github-zbx/ava_datasets

AVA-ActiveSpeaker: An Audio-Visual Dataset for Active Speaker Detection

https://github.com/johanattia/tensorflow-saint

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

https://github.com/jrzaurin/pytorch-widedeep

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

https://github.com/kaistmm/TalkNCE

LoCoNet: Long-Short Context Network for Active Speaker Detection

https://github.com/kaize0409/GPN_Graph-Few-shot

Graph Prototypical Networks for Few-shot Learning on Attributed Networks

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