Papers with Code 아카이브

Active Speaker Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

1

보존된 평가 기록

1

코드

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

https://github.com/lewis-od/QNN

Continuous-variable quantum neural networks

https://github.com/lucidrains/tab-transformer-pytorch/tree/main/tab_transformer_pytorch

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

https://github.com/mala-lab/anomalygfm

Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements

https://github.com/mingboiz/social_network_analysis_birank

Social network analytics for supervised fraud detection in insurance

https://github.com/ogunlao/saint

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

https://github.com/pygod-team/pygod

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction

https://github.com/robeespi/Deep-Semi-supervised-intrusion-detection-on-Hadoop-distributed-file-system-log

Deep Anomaly Detection with Deviation Networks

https://github.com/robeespi/Deep-Semi-supervised-intrusion-detection-on-unstructured-Hadoop-distributed-file-system-logs

Deep Anomaly Detection with Deviation Networks

https://github.com/robeespi/Weakly-Supervised-Malware-Detection

Deep Anomaly Detection with Deviation Networks

https://github.com/ronaldpereira/pick-and-choose-gnn

How effective are Graph Neural Networks in Fraud Detection for Network Data?

https://github.com/safe-graph/DGFraud/tree/master/algorithms/SemiGNN

A Semi-supervised Graph Attentive Network for Financial Fraud Detection

https://github.com/safe-graph/dgfraud-tf2

Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

https://github.com/smrjan/predictive-maintainance

A Survey of Predictive Modelling under Imbalanced Distributions

https://github.com/sophchoe/Binary_Classification_Pennylane_Keras

Continuous-variable quantum neural networks

https://github.com/sophchoe/Hybrid-Quantum-Classical-MNIST-Classfication-Model

Continuous-variable quantum neural networks

https://github.com/sophchoe/QML

Continuous-variable quantum neural networks

https://github.com/sophchoe/continous-variable-quantum-mnist-classifiers

Continuous-variable quantum neural networks

https://github.com/split-gnn/splitgnn

https://github.com/taoruijie/talknet-asd

Is Someone Speaking? Exploring Long-term Temporal Features for Audio-visual Active Speaker Detection

https://github.com/thirdairesearch/bolt_benchmarks

BOLT: An Automated Deep Learning Framework for Training and Deploying Large-Scale Search and Recommendation Models on Commodity CPU Hardware

https://github.com/thudm/graphcad

Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

https://github.com/tusharsarkar3/XBNet

XBNet : An Extremely Boosted Neural Network

https://github.com/vinayakumarr/Deep-Net

Deep-Net: Deep Neural Network for Cyber Security Use Cases

https://github.com/wdhyun/LEX-GNN

https://github.com/xinleihe/link_stealing_attack

Stealing Links from Graph Neural Networks

https://github.com/xuhongzuo/DeepOD

Deep Anomaly Detection with Deviation Networks

https://github.com/yangyucheng000/Paper-3/tree/main/bi-crypto-nets-mindspore-master

Crypto Pump and Dump via Deep Learning Techniques

https://github.com/yzhao062/yzhao062

TOD: GPU-accelerated Outlier Detection via Tensor Operations

https://github.com/zaheerkhancs/QuantumNeuralNetwork

Continuous-variable quantum neural networks

https://github.com/zcxu-eric/Ego4d_TalkNet_ASD

Is Someone Speaking? Exploring Long-term Temporal Features for Audio-visual Active Speaker Detection

https://github.com/zjunet/amnet

Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

https://gitlab.com/SCoRe-Group/SABNA-Release

Scalable Exact Parent Sets Identification in Bayesian Networks Learning with Apache Spark

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