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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/c2dc/anomaly-flow

공식 코드

Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service Detection

https://github.com/caganselim/tltm

공식 코드

Two-Level Temporal Relation Model for Online Video Instance Segmentation

https://github.com/cairo-thws/fedacrossplus

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Domain Borders Are There to Be Crossed With Federated Few-Shot Adaptation

https://github.com/camlab-ethz/rigno

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RIGNO: A Graph-based framework for robust and accurate operator learning for PDEs on arbitrary domains

https://github.com/camma-public/hpe-adaptor

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Unsupervised domain adaptation for clinician pose estimation and instance segmentation in the operating room

https://github.com/cardio-ai/funavg

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FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels

https://github.com/carocciluca/gnn-site-selection

공식 코드

Optimizing Luxury Vehicle Dealership Networks: A Graph Neural Network Approach to Site Selection

https://github.com/carrierlxk/AGNN

공식 코드

Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks

https://github.com/cedricvincentcuaz/TFGW

공식 코드

Template based Graph Neural Network with Optimal Transport Distances

https://github.com/cedricwangyu/dpnf

공식 코드

Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records

https://github.com/cgoliver/rnaglib

공식 코드

A Comprehensive Benchmark for RNA 3D Structure-Function Modeling

https://github.com/chaitjo/geometric-rna-design

공식 코드

gRNAde: Geometric Deep Learning for 3D RNA inverse design

https://github.com/changminwu/expandergnn

공식 코드

Sparsifying the Update Step in Graph Neural Networks

https://github.com/chao1224/n_gram_graph

공식 코드

N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules

https://github.com/chao1224/sgnn-ebm

공식 코드

Structured Multi-task Learning for Molecular Property Prediction

https://github.com/chaoyanghe/bipartite-graph-learning

공식 코드

Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs

https://github.com/chasesecurity/spamdam

공식 코드

SpamDam: Towards Privacy-Preserving and Adversary-Resistant SMS Spam Detection

https://github.com/cheikh025/DistrictNet

공식 코드

DistrictNet: Decision-aware learning for geographical districting

https://github.com/chenfengzhao/gnnhls

공식 코드

GNNHLS: Evaluating Graph Neural Network Inference via High-Level Synthesis

https://github.com/chengzhag/DeepPanoContext

공식 코드

DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization

https://github.com/chengzhag/Implicit3DUnderstanding

공식 코드

Holistic 3D Scene Understanding from a Single Image with Implicit Representation

https://github.com/chengzhepiao/coldstartbglp

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Privacy Preserved Blood Glucose Level Cross-Prediction: An Asynchronous Decentralized Federated Learning Approach

https://github.com/chenjie20/SSCDL

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Conditional Distribution Learning on Graphs

https://github.com/chenxx89/bfrffusion

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Towards Real-World Blind Face Restoration with Generative Diffusion Prior

https://github.com/chenzhaiyu/polygnn

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PolyGNN: Polyhedron-based Graph Neural Network for 3D Building Reconstruction from Point Clouds

https://github.com/chenzrg/behrmecom

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BernGraph: Probabilistic Graph Neural Networks for EHR-based Medication Recommendations

https://github.com/chiamuyu/PI-Net

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Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics

https://github.com/chiang-yuan/prodar

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Encoding protein dynamic information in graph representation for functional residue identification

https://github.com/chinmay5/ms_ida

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Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images

https://github.com/chisam0217/Graph-Universal-Attack

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Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models

https://github.com/choderalab/espaloma_charge

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EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment

https://github.com/chrisbloecker/neuromap

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The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks

https://github.com/chrisdxie/rice

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RICE: Refining Instance Masks in Cluttered Environments with Graph Neural Networks

https://github.com/chrisjtan/gnn_cff

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Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning

https://github.com/chriskuei/fedmatch

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FedMatch: Federated Learning Over Heterogeneous Question Answering Data

https://github.com/christianlebeda/plan-experiments

공식 코드

PLAN: Variance-Aware Private Mean Estimation

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