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Privacy Preserving

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

https://github.com/tharaka-perera/flex-net

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Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex Networks

https://github.com/thejonaslab/vonmises-icml-2023

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Von Mises Mixture Distributions for Molecular Conformation Generation

https://github.com/thejungwon/gc-fed

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GC-Fed: Gradient Centralized Federated Learning with Partial Client Participation

https://github.com/themarcosf/mech-interp-paper

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Mechanistic Interpretability in the Presence of Architectural Obfuscation

https://github.com/thisisforreview/svd-gcn

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A Simple Yet Effective SVD-GCN for Directed Graphs

https://github.com/thudm/graphcad

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Graph Contrastive Learning for Anomaly Detection

https://github.com/thumnlab/nas-bench-graph

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NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search

https://github.com/thunlp/GNNPapers

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Graph Neural Networks: A Review of Methods and Applications

https://github.com/thunlp/MuGNN

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Multi-Channel Graph Neural Network for Entity Alignment

https://github.com/thupchnsky/sc_mvae

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Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls

https://github.com/thuwangcy/directau

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Towards Representation Alignment and Uniformity in Collaborative Filtering

https://github.com/tianshu-wang/pfs-gnn-bipartite

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Graph Neural Network-based Resource Allocation Strategies for Multi-Object Spectroscopy

https://github.com/tiiuae/gnn-jamming-source-localization

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Graph Neural Networks for Jamming Source Localization

https://github.com/timd3/moco

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Moco: A Learnable Meta Optimizer for Combinatorial Optimization

https://github.com/timpostuvan/adagrid

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AdaGrid: Adaptive Grid Search for Link Prediction Training Objective

https://github.com/tjpaik/invariantrepresentation

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Invariant Representations of Embedded Simplicial Complexes

https://github.com/tjrudrnr2/PRISM_ICLR25

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PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models

https://github.com/tkforgeron/ocppm

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HOEG: A New Approach for Object-Centric Predictive Process Monitoring

https://github.com/tkgsn/p3gm

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P3GM: Private High-Dimensional Data Release via Privacy Preserving Phased Generative Model

https://github.com/tkipf/c-swm

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Contrastive Learning of Structured World Models

https://github.com/tlmakinen/cosmicgraphs

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The Cosmic Graph: Optimal Information Extraction from Large-Scale Structure using Catalogues

https://github.com/tmcarvalho/AUTOPRIV

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Automated Privacy-Preserving Techniques via Meta-Learning

https://github.com/tmcarvalho/privatesmote

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Differentially-Private Data Synthetisation for Efficient Re-Identification Risk Control

https://github.com/toenshoff/runcsp-pytorch

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One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction

https://github.com/toggled/FvFGeo

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Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation

https://github.com/tolusophy/polykervnets

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Regularized PolyKervNets: Optimizing Expressiveness and Efficiency for Private Inference in Deep Neural Networks

https://github.com/tommy-qichang/AsynDGAN

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Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data

https://github.com/tommydzh/diam

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Effective Illicit Account Detection on Large Cryptocurrency MultiGraphs

https://github.com/tongxu-05/regnn-multiple-appropriate-facial-reaction-generation

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Reversible Graph Neural Network-based Reaction Distribution Learning for Multiple Appropriate Facial Reactions Generation

https://github.com/trachote/crystalgrw

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CrystalGRW: Generative Modeling of Crystal Structures with Targeted Properties via Geodesic Random Walks

https://github.com/trainsn/gnn-surrogate

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GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations

https://github.com/trucndt/ami

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Active Membership Inference Attack under Local Differential Privacy in Federated Learning

https://github.com/trueWangSyutung/UFGraphFR

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UFGraphFR: An attempt at a federated recommendation system based on user text characteristics

https://github.com/trust-tuda/crowdguard

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CrowdGuard: Federated Backdoor Detection in Federated Learning

https://github.com/trusthlt/acl2022-reparametrization-trick-broke-differential-privacy

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How reparametrization trick broke differentially-private text representation learning

https://github.com/trusthlt/dp-across-nlp-tasks

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One size does not fit all: Investigating strategies for differentially-private learning across NLP tasks

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