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Active Speaker Detection

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

https://github.com/bdi-lab/monti

공식 코드

Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors

https://github.com/bigdyl-yonsei/OCTGAN

공식 코드

OCT-GAN: Neural ODE-based Conditional Tabular GANs

https://github.com/boschresearch/graphlevel-anomalydetection

공식 코드

Raising the Bar in Graph-level Anomaly Detection

https://github.com/boxinz17/data-market-via-adaptive-sampling

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Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm

https://github.com/campanulabells/huge-gad

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A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection

https://github.com/cchao0116/EasyDGL

공식 코드

EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning

https://github.com/clovaai/lookwhostalking

공식 코드

Look Who's Talking: Active Speaker Detection in the Wild

https://github.com/compnet/pang

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Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurement

https://github.com/cvjena/libmaxdiv

공식 코드

Detecting Regions of Maximal Divergence for Spatio-Temporal Anomaly Detection

https://github.com/davidnugent2425/he-cc-fraud-detection

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Privacy-Preserving Credit Card Fraud Detection using Homomorphic Encryption

https://github.com/dberghi/leveraging-visual-supervision-for-array-based-asdl

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Leveraging Visual Supervision for Array-based Active Speaker Detection and Localization

https://github.com/dcszhang/dynamic_feature

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Dynamic Feature Fusion: Combining Global Graph Structures and Local Semantics for Blockchain Fraud Detection

https://github.com/deeksha-sethi03/nl-imbalanced-learning

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Neurochaos Feature Transformation and Classification for Imbalanced Learning

https://github.com/derposoft/crypto_pump_and_dump_with_deep_learning

공식 코드

Crypto Pump and Dump via Deep Learning Techniques

https://github.com/dhivyaeswaran/hols

공식 코드

Higher-Order Label Homogeneity and Spreading in Graphs

https://github.com/dingdingding60/humanoids2024hri

공식 코드

Imitation of human motion achieves natural head movements for humanoid robots in an active-speaker detection task

https://github.com/dmlc/dgl

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DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs

https://github.com/donghao51/nng-mix

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NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly Generation

https://github.com/ds3lab/dyhgn

공식 코드

Modelling graph dynamics in fraud detection with "Attention"

https://github.com/eBay/xFraud

공식 코드

xFraud: Explainable Fraud Transaction Detection

https://github.com/elopezfune/urysohn-s-binary-classifier

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Leveraging the Urysohn Lemma of Topology for an Enhanced Binary Classifier

https://github.com/facebookresearch/taser-tgnn

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TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning

https://github.com/fdjingliu/dmad

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A Survey on Diffusion Models for Anomaly Detection

https://github.com/featurespace/foundation-model-paper

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Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences

https://github.com/feedzai/bank-account-fraud

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

https://github.com/feedzai/deccaf

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Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints

https://github.com/feedzai/fair-automl

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Promoting Fairness through Hyperparameter Optimization

https://github.com/feedzai/fifar-dataset

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FiFAR: A Fraud Detection Dataset for Learning to Defer

https://github.com/feedzai/research-arms

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ARMS: Automated rules management system for fraud detection

https://github.com/feedzai/timeshap

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TimeSHAP: Explaining Recurrent Models through Sequence Perturbations

https://github.com/fingertap/fird.cython

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Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework

https://github.com/finint/antifraud

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Semi-supervised Credit Card Fraud Detection via Attribute-Driven Graph Representation

https://github.com/flopska/mmdew-change-detector

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Maximum Mean Discrepancy on Exponential Windows for Online Change Detection

https://github.com/foobar777x/ja-gnn-exp

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Financial Fraud Detection using Jump-Attentive Graph Neural Networks

https://github.com/freshmanxb/dbdt

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Efficient Fraud Detection Using Deep Boosting Decision Trees

https://github.com/fuankarion/active-speakers-context

공식 코드

Active Speakers in Context

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