https://github.com/AIM-IT4/Topological-Risk-Measure-for-Derivatives
공식 코드Beyond VaR and CVaR: Topological Risk Measures in Financial Markets
Papers with Code 아카이브
2-task Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BorgwardtLab/Neural-Persistence
공식 코드Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
https://github.com/BorgwardtLab/topological-autoencoders
공식 코드https://github.com/Brian-hongyan/DEG-substance-addiction
공식 코드Multiscale Topology in Interactomic Network: From Transcriptome to Antiaddiction Drug Repurposing
https://github.com/CSU-TDA/PersistenceImages
공식 코드Persistence Images: A Stable Vector Representation of Persistent Homology
https://github.com/ChenLiu-1996/CUTS
공식 코드https://github.com/Chrisa142857/neuro_detour
공식 코드NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes
https://github.com/DavideBuffelli/CliquePH
공식 코드https://github.com/DeepK/distance-embed
공식 코드Unsupervised Sentence-embeddings by Manifold Approximation and Projection
https://github.com/HS-Ansbach-CCS/dyca
공식 코드https://github.com/Lihaogx/DNDN
공식 코드Dynamic Neural Dowker Network: Approximating Persistent Homology in Dynamic Directed Graphs
https://github.com/LuisScoccola/persistable
공식 코드Stable and consistent density-based clustering via multiparameter persistence
https://github.com/MathieuCarriere/perslay
공식 코드PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
https://github.com/PariSolunke/mountaineer
공식 코드MOUNTAINEER: Topology-Driven Visual Analytics for Comparing Local Explanations
https://github.com/RabadanLab/TARGet
공식 코드Inference of Ancestral Recombination Graphs through Topological Data Analysis
https://github.com/RitAreaSciencePark/ZigZagLLMs
공식 코드https://github.com/Saumya-Gupta-26/TopoDiffusionNet
공식 코드https://github.com/Saumya-Gupta-26/struct-uncertainty
공식 코드https://github.com/Snopoff/Vulnerability-Detection-via-Topological-Analysis-of-Attention-Maps
공식 코드Vulnerability Detection via Topological Analysis of Attention Maps
https://github.com/USFDataVisualization/MapperOnGraphs
공식 코드Homology-Preserving Multi-Scale Graph Skeletonization Using Mapper on Graphs
https://github.com/UlysseCoteAllard/sEMG_handCraftedVsLearnedFeatures
공식 코드Interpreting Deep Learning Features for Myoelectric Control: A Comparison with Handcrafted Features
https://github.com/YueqiCao/PD-subsample
공식 코드https://github.com/ZC119/PB
공식 코드https://github.com/a-zeg/ellipsoids
공식 코드https://github.com/abrochar/pp_syn
공식 코드Particle gradient descent model for point process generation
https://github.com/adauchendu/awesometda4nlp
공식 코드https://github.com/adauchendu/topformer
공식 코드TOPFORMER: Topology-Aware Authorship Attribution of Deepfake Texts with Diverse Writing Styles
https://github.com/adines/ttassl
공식 코드https://github.com/aidos-lab/CFGGME
공식 코드https://github.com/andrespollano/neural_nets-tda
공식 코드Detecting out-of-distribution text using topological features of transformer-based language models
https://github.com/ansonb/knowledge_persistence
공식 코드https://github.com/antheamonod/Dilation_invariant_bottleneck
공식 코드Topological Information Retrieval with Dilation-Invariant Bottleneck Comparative Measures
https://github.com/antonfrancois/gliomasegmentation_tda
공식 코드Train-Free Segmentation in MRI with Cubical Persistent Homology
https://github.com/appliedtopology/gcc
공식 코드https://github.com/architrathore/TopoAct
공식 코드TopoAct: Visually Exploring the Shape of Activations in Deep Learning
https://github.com/asgeorges/mapper-classifier
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.