Papers with Code 아카이브

Privacy Preserving

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/imfusiongmbh/vid-vertebra-identification-dataset

공식 코드

Robust vertebra identification using simultaneous node and edge predicting Graph Neural Networks

https://github.com/imguangyu/fedcola

공식 코드

Towards Multi-modal Transformers in Federated Learning

https://github.com/inathwor/Preempting-Text-Sanitization

공식 코드

Preempting Text Sanitization Utility in Resource-Constrained Privacy-Preserving LLM Interactions

https://github.com/info-ucr/peftleak

공식 코드

Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning

https://github.com/ink-usc/sparse-distillation

공식 코드

Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models

https://github.com/intellabs/matsciml

공식 코드

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

https://github.com/intelligentgeometry/gegnn

공식 코드

Learning the Geodesic Embedding with Graph Neural Networks

https://github.com/intelligolabs/privacy-gtd-3d

공식 코드

Upper-Body Pose-based Gaze Estimation for Privacy-Preserving 3D Gaze Target Detection

https://github.com/ipadli/grasper

공식 코드

Grasper: A Generalist Pursuer for Pursuit-Evasion Problems

https://github.com/irmvlab/rlsac

공식 코드

RLSAC: Reinforcement Learning enhanced Sample Consensus for End-to-End Robust Estimation

https://github.com/irvingmeng/securevector

공식 코드

Towards Privacy-Preserving, Real-Time and Lossless Feature Matching

https://github.com/isee-laboratory/pixelfade

공식 코드

PixelFade: Privacy-preserving Person Re-identification with Noise-guided Progressive Replacement

https://github.com/islamazhar/compact-public

공식 코드

Compact: Approximating Complex Activation Functions for Secure Computation

https://github.com/ispras/gnn-aid

공식 코드

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense

https://github.com/isvy08/l2c

공식 코드

Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations

https://github.com/itsnotacie/nn-fedkd-hybrid

공식 코드

FedKD-hybrid: Federated Hybrid Knowledge Distillation for Lithography Hotspot Detection

https://github.com/itssmutnuri/gnnvariants

공식 코드

Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks

https://github.com/itsukifujii/attrgau

공식 코드

Enhancing Attributed Graph Networks with Alignment and Uniformity Constraints for Session-based Recommendation

https://github.com/itu-ai-ml-in-5g-challenge/itu-ml5g-ps-001-parana

공식 코드

QT-Routenet: Improved GNN generalization to larger 5G networks by fine-tuning predictions from queueing theory

https://github.com/ivam-he/BernNet

공식 코드

BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation

https://github.com/ivanniu/inversiongnn

공식 코드

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization

https://github.com/iyempissy/privgnn

공식 코드

Releasing Graph Neural Networks with Differential Privacy Guarantees

https://github.com/j-cap/FL-based-neural-FF-control

공식 코드

Federated Learning for Privacy-Preserving Feedforward Control in Multi-Agent Systems

https://github.com/j-f-cheng/g-fars-3dpartgrouping

공식 코드

G-FARS: Gradient-Field-based Auto-Regressive Sampling for 3D Part Grouping

https://github.com/jaabmar/private-pgd

공식 코드

Privacy-preserving data release leveraging optimal transport and particle gradient descent

https://github.com/jack24658735/fedlgt

공식 코드

Language-Guided Transformer for Federated Multi-Label Classification

https://github.com/jacklinkk/torchgrl

공식 코드

Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments

https://github.com/jadecurl/predicting-viral-rumors-and-vulnerable-users

공식 코드

Predicting Viral Rumors and Vulnerable Users for Infodemic Surveillance

https://github.com/jahirsadik/cohet-implementation

공식 코드

Enhancing Heterogeneous Multi-Agent Cooperation in Decentralized MARL via GNN-driven Intrinsic Rewards

https://github.com/jakub-zarzycki2022/gattaca

공식 코드

Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks: The GATTACA Framework

https://github.com/james-flemings/dp_compress

공식 코드

Differentially Private Knowledge Distillation via Synthetic Text Generation

https://github.com/jamesyifan/DisenHAN

공식 코드

DisenHAN: Disentangled Heterogeneous Graph Attention Network for Recommendation

https://github.com/jarrycyx/unn

공식 코드

CUTS: Neural Causal Discovery from Irregular Time-Series Data

https://github.com/jasonzy121/TextGNN

공식 코드

TextGNN: Improving Text Encoder via Graph Neural Network in Sponsored Search

https://github.com/jbcdnr/gretel-path-extrapolation

공식 코드

Extrapolating paths with graph neural networks

https://github.com/jcastro295/gegengnn

공식 코드

Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction

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