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Bayesian Inference

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보존된 평가 기록: 2

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/HerculesJack/bayesfast

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Normalizing Constant Estimation with Gaussianized Bridge Sampling

https://github.com/HeyuanMingong/llirl

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Lifelong Incremental Reinforcement Learning with Online Bayesian Inference

https://github.com/IndustAI/risk-and-uncertainty

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Estimating Risk and Uncertainty in Deep Reinforcement Learning

https://github.com/IraKorshunova/bruno

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BRUNO: A Deep Recurrent Model for Exchangeable Data

https://github.com/JamesMalkin/EfficientBayes

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Signatures of Bayesian inference emerge from energy efficient synapses

https://github.com/JeremiasKnoblauch/GVIPublic

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Generalized Variational Inference: Three arguments for deriving new Posteriors

https://github.com/JiaxiLi1/Online-Learning-Differentiable-Partiacle-Filters

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Learning Differentiable Particle Filter on the Fly

https://github.com/JoeriHermans/constraining-dark-matter-with-stellar-streams-and-ml

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Towards constraining warm dark matter with stellar streams through neural simulation-based inference

https://github.com/Kim-Dongjun/Posterior_Aided_Regularization_for_Likelihood_Free_Inference

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Neural Posterior Regularization for Likelihood-Free Inference

https://github.com/Kim-Dongjun/Sequential_Likelihood_Free_Inference_with_Implicit_Surrogate_Proposal

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Sequential Likelihood-Free Inference with Neural Proposal

https://github.com/KingSpencer/DBULL

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Deep Bayesian Unsupervised Lifelong Learning

https://github.com/KordingLab/adversarial-wake-sleep

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Learning to infer in recurrent biological networks

https://github.com/LaurenceA/adabayes

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Bayesian filtering unifies adaptive and non-adaptive neural network optimization methods

https://github.com/LeviBorodenko/motionblur

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Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference

https://github.com/LoryPack/SM-ExpFam-LFI

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Score Matched Neural Exponential Families for Likelihood-Free Inference

https://github.com/LuSchumacher/dynamic_ddm

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Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive Models

https://github.com/MIRALab-USTC/RL-TRACER

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Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions

https://github.com/MaStatLab/WARP

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Learning Asymmetric and Local Features in Multi-Dimensional Data through Wavelets with Recursive Partitioning

https://github.com/MichaelCBrennan/lazymaps

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Greedy inference with structure-exploiting lazy maps

https://github.com/Microsoft/vi-hds

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Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems

https://github.com/MingzhouFan97/PGPS

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Path-Guided Particle-based Sampling

https://github.com/MrinankSharma/DP-PVI

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Differentially Private Federated Variational Inference

https://github.com/MrtnMndt/OCDVAEContinualLearning

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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

https://github.com/MrtnMndt/OCDVAE_ContinualLearning

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Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

https://github.com/Nars98/PSD

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The Polynomial Stein Discrepancy for Assessing Moment Convergence

https://github.com/Neclow/bayesian_phylo_distances

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Generalised Bayesian distance-based phylogenetics for the genomics era

https://github.com/NeuromorphicComputing/SoftHebb

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SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks

https://github.com/Nisha1803/Methodology_Endosomal_Escape

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Stochastic Model of siRNA Endosomal Escape Mediated by Fusogenic Peptides in OVCAR-3

https://github.com/Numb3rs-UTS/Robust-Ranking-Aggregation--CoarsenRank

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Fast and Robust Rank Aggregation against Model Misspecification

https://github.com/PedroRASB/COVID-19-detection-with-lung-segmentation

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COVID-19 detection using chest X-rays: is lung segmentation important for generalization?

https://github.com/PredictiveIntelligenceLab/BayesianDifferentiableProgramming

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Bayesian differential programming for robust systems identification under uncertainty

https://github.com/PredictiveIntelligenceLab/GP-NODEs

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Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data

https://github.com/Priesemann-Group/covid19_inference_forecast

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Inferring COVID-19 spreading rates and potential change points for case number forecasts

https://github.com/QHwan/PretrainDPI

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Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interaction

https://github.com/RPD123-byte/Demonstrating-the-Continual-Learning-Capabilities-and-Practical-Application-of-Discrete-Time-Active

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Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active Inference

https://github.com/RSNirwan/HouseholderBPCA

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Rotation Invariant Householder Parameterization for Bayesian PCA

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