https://github.com/3sigmalab/SINDyG
공식 코드SINDyG: Sparse Identification of Nonlinear Dynamical Systems from Graph-Structured Data
Papers with Code 아카이브
Epidemiology
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Epidemiology is a scientific discipline that provides reliable knowledge for clinical medicine focusing on prevention, diagnosis and treatment of diseases. Research in Epidemiology aims at characterizing risk factors for the outbreak of diseases and at evaluating the efficiency of certain treatment strategies, e.g., to compare a new treatment with an established gold standard. This research is strongly hypothesis-driven and statistical analysis is the major tool for epidemiologists so far. Correlations between genetic factors, environmental factors, life style-related parameters, age and diseases are analyzed.
Source: Visual Analytics of Image-Centric Cohort Studies in Epidemiology
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AliAlkadhim/ALFFI
공식 코드Amortized Simulation-Based Frequentist Inference for Tractable and Intractable Likelihoods
https://github.com/AliciaCurth/IF-learn
공식 코드Estimating Structural Target Functions using Machine Learning and Influence Functions
https://github.com/HazyResearch/mandoline
공식 코드https://github.com/HsiangHsu/2019-AISTATS-CA
공식 코드https://github.com/LingsongMeng/GuidedSparseKmeans
공식 코드https://github.com/LuisEVT/COVID19_Cost_Effectiveness_Of_Control_Measures
공식 코드Cost Effective Reproduction Number Based Strategies for Reducing Deaths from COVID-19
https://github.com/Mandar-Sharma/TCube
공식 코드https://github.com/Matthew-Ryan1995/BaD_testing_and_isolation
공식 코드https://github.com/NThakkar-IDM/covid_and_stat_mech
공식 코드COVID-19 epidemiology as emergent behavior on a dynamic transmission forest
https://github.com/OgPlexus/Asymptomatic1
공식 코드Optimal virulence strategies in epidemiological models with asymptomatic transmission
https://github.com/SABS-R3-Epidemiology/epiabm
공식 코드https://github.com/SmarTreatMate/SmarTreatMate.github.io
공식 코드Using Geographic Location-based Public Health Features in Survival Analysis
https://github.com/SwissTPH/openmalaria
공식 코드https://github.com/WenjieZ/2019-nCoV
공식 코드Total Variation Regularization for Compartmental Epidemic Models with Time-Varying Dynamics
https://github.com/adhalanay/epidemiology_crns
공식 코드Stability in Reaction Network Models via an Extension of the Next Generation Matrix Method
https://github.com/adityalab/gradabm
공식 코드https://github.com/ahb48/neighbourhoods_and_households
공식 코드Epidemiological dynamics in populations structured by neighbourhoods and households
https://github.com/ajvish91/covid_twitter_scripts
공식 코드COVID-19 Twitter Dataset with Latent Topics, Sentiments and Emotions Attributes
https://github.com/algebraicjulia/stockflow.jl
공식 코드A Categorical Framework for Modeling with Stock and Flow Diagrams
https://github.com/antti-pollanen/ci_noisy_treatment
공식 코드Identifiable causal inference with noisy treatment and no side information
https://github.com/atlantac96/LF-GO-OED
공식 코드A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design
https://github.com/aurelien-pelissier/regir
공식 코드https://github.com/boschresearch/local_neural_transformations
공식 코드Detecting Anomalies within Time Series using Local Neural Transformations
https://github.com/brightmanu-lang/spn-param-recovery
공식 코드A Simple Approximate Bayesian Inference Neural Surrogate for Stochastic Petri Net Models
https://github.com/calakus/covregrf
공식 코드https://github.com/cevo-public/lapis
공식 코드LAPIS is a fast web API for massive open virus sequencing databases
https://github.com/changzong/STCAD
공식 코드Structural-Temporal Coupling Anomaly Detection with Dynamic Graph Transformer
https://github.com/costantinobudroni/opt-disease-control
공식 코드https://github.com/damnets/damnets_icml_2022
공식 코드DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series
https://github.com/davidrburt/lipschitz-driven-inference
공식 코드Smooth Sailing: Lipschitz-Driven Uncertainty Quantification for Spatial Association
https://github.com/dennisprangle/distillingimportancesampling
공식 코드Distilling Importance Sampling for Likelihood Free Inference
https://github.com/emory-irlab/PHM2017
공식 코드https://github.com/emory-melody/awesome-epidemic-modeling-papers
공식 코드https://github.com/emory-melody/epilearn
공식 코드Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph
https://github.com/facebookresearch/neural_stpp
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.