https://github.com/cassidylaidlaw/boltzmann-policy-distribution
공식 코드The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models
Papers with Code 아카이브
Bayesian Inference
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/cdb342/ijcai-2022-zla
공식 코드https://github.com/ceadpx/neural_operators
공식 코드From Theory to Application: A Practical Introduction to Neural Operators in Scientific Computing
https://github.com/cedricwangyu/nofas
공식 코드https://github.com/chang-ml-thu/AWGF
공식 코드Understanding and Accelerating Particle-Based Variational Inference
https://github.com/changhoonhahn/sedflow
공식 코드Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation
https://github.com/changliu00/Riem-SVGD
공식 코드Riemannian Stein Variational Gradient Descent for Bayesian Inference
https://github.com/changwoo-lee/TLOHO
공식 코드T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs
https://github.com/charlesm93/amortized_vi
공식 코드https://github.com/charlesm93/avi-when-and-why
공식 코드https://github.com/charlesm93/vi_location_robust
공식 코드Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
https://github.com/chengzhang-uci/RNSHMC
공식 코드Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases
https://github.com/chenw20/sgpa
공식 코드https://github.com/chenyujie1104/exponentialgm
공식 코드https://github.com/chijan-nh/LearningCoefficient-RLCT-ofLDA-usingGS
공식 코드The Exact Asymptotic Form of Bayesian Generalization Error in Latent Dirichlet Allocation
https://github.com/chrhenning/uncertainty_based_ood
공식 코드On out-of-distribution detection with Bayesian neural networks
https://github.com/chris-nemeth/sgmcmc-review-paper
공식 코드https://github.com/chriscarmona/aistats2020smi
공식 코드https://github.com/chriscarmona/modularbayes
공식 코드Scalable Semi-Modular Inference with Variational Meta-Posteriors
https://github.com/christiaanjs/treeflow
공식 코드TreeFlow: probabilistic programming and automatic differentiation for phylogenetics
https://github.com/christiando/dynamic_ising
공식 코드Inverse Ising problem in continuous time: A latent variable approach
https://github.com/cics-nd/predictive-cvs
공식 코드Predictive Collective Variable Discovery with Deep Bayesian Models
https://github.com/claassengroup/matLeap
공식 코드matLeap: A fast adaptive Matlab-ready tau-leaping implementation suitable for Bayesian inference
https://github.com/clbonet/Sliced-Wasserstein_Gradient_Flows
공식 코드https://github.com/clear-nus/ncdssm
공식 코드Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
https://github.com/clelidm/MinCompSpin
공식 코드Bayesian Inference of Minimally Complex Models with Interactions of Arbitrary Order
https://github.com/cobypenso/functional_ensemble_distillation
공식 코드https://github.com/coco66/ADFQ
공식 코드https://github.com/colehawkins/ksd-thinning
공식 코드Online, Informative MCMC Thinning with Kernelized Stein Discrepancy
https://github.com/cpempire/pSVGD
공식 코드https://github.com/cpempire/pWGD
공식 코드Projected Wasserstein gradient descent for high-dimensional Bayesian inference
https://github.com/ctu-vras/actsel
공식 코드https://github.com/danielward27/pyrox
공식 코드SoftCVI: Contrastive variational inference with self-generated soft labels
https://github.com/danielward27/softcvi
공식 코드SoftCVI: Contrastive variational inference with self-generated soft labels
https://github.com/danielward27/softcvi_validation
공식 코드SoftCVI: Contrastive variational inference with self-generated soft labels
https://github.com/dannyfa/inflationary_flows
공식 코드Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.