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Privacy Preserving
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/trusthlt/dp-rewrite
공식 코드DP-Rewrite: Towards Reproducibility and Transparency in Differentially Private Text Rewriting
https://github.com/trusthlt/privacy-legal-nlp-lm
공식 코드Privacy-Preserving Models for Legal Natural Language Processing
https://github.com/trusthlt/privacy-preserving-gcn
공식 코드Privacy-Preserving Graph Convolutional Networks for Text Classification
https://github.com/tsinghua-fib-lab/grape
공식 코드https://github.com/tsinghua-fib-lab/graph-denoising-socialrec
공식 코드Robust Preference-Guided Denoising for Graph based Social Recommendation
https://github.com/tsinghua-fib-lab/kdd2023-id546-urbaninfra
공식 코드Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network
https://github.com/tsinghua-fib-lab/pategail
공식 코드PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation Learning
https://github.com/tsinghua-fib-lab/road-planning-for-slums
공식 코드https://github.com/tsingz0/dbe
공식 코드Eliminating Domain Bias for Federated Learning in Representation Space
https://github.com/tsubasat/P3GM
공식 코드P3GM: Private High-Dimensional Data Release via Privacy Preserving Phased Generative Model
https://github.com/tsurubee/deepcrystet
공식 코드https://github.com/tsy935/eeg-gnn-ssl
공식 코드Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis
https://github.com/tsy935/graphs4mer
공식 코드Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models
https://github.com/tsy935/readmit-stgnn
공식 코드https://github.com/ttliu98/fedrkg
공식 코드FedRKG: A Privacy-preserving Federated Recommendation Framework via Knowledge Graph Enhancement
https://github.com/tudelft-spc-lab/conflab
공식 코드https://github.com/tufts-ml/patchgt
공식 코드PatchGT: Transformer over Non-trainable Clusters for Learning Graph Representations
https://github.com/tum-aimed/hyfed
공식 코드HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning
https://github.com/tumftm/radargnn
공식 코드RadarGNN: Transformation Invariant Graph Neural Network for Radar-based Perception
https://github.com/tummfm/chemtrain
공식 코드https://github.com/tummfm/resolv
공식 코드Predicting solvation free energies with an implicit solvent machine learning potential
https://github.com/tuneinsight/federated-llms
공식 코드Mitigating Unintended Memorization with LoRA in Federated Learning for LLMs
https://github.com/turboLJY/CapsGNN-Review-Generation
공식 코드Knowledge-Enhanced Personalized Review Generation with Capsule Graph Neural Network
https://github.com/tw-repository/asyrec
공식 코드https://github.com/txie-93/polymernet
공식 코드https://github.com/typilus/typilus
공식 코드https://github.com/uJ62JHD/Privacy-Preserving-Social-Network-Embedding
공식 코드Adversarial Privacy Preserving Graph Embedding against Inference Attack
https://github.com/uber/MARVIN
공식 코드https://github.com/ubiquitouslearning/fes
공식 코드https://github.com/ucamrl/xrlflow
공식 코드X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation
https://github.com/ucf-lou-lab-pet/cipher-prune-inference
공식 코드CipherPrune: Efficient and Scalable Private Transformer Inference
https://github.com/uclasystem/dorylus
공식 코드https://github.com/ucsd-hep-ex/GraphAE
공식 코드Particle Graph Autoencoders and Differentiable, Learned Energy Mover's Distance
https://github.com/ucuapps/openglue
공식 코드OpenGlue: Open Source Graph Neural Net Based Pipeline for Image Matching
https://github.com/ufal/mrpipe-conll2019
공식 코드ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared Task
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.