https://bitbucket.org/doglic/asr
공식 코드Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural Networks
Papers with Code 아카이브
Bayesian Inference
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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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://bitbucket.org/dtolpin/spp-studies
공식 코드https://bitbucket.org/dtolpin/stochastic-conditioning
공식 코드https://bitbucket.org/jhhuggins/lrcoresets
공식 코드https://bitbucket.org/jhhuggins/random-feature-stein-discrepancies
공식 코드https://git.skewed.de/count0/graph-tool
공식 코드Nonparametric Bayesian inference of the microcanonical stochastic block model
https://github.com/4ment/torchtree
공식 코드Torchtree: flexible phylogenetic model development and inference using PyTorch
https://github.com/4ment/torchtree-experiments
공식 코드Torchtree: flexible phylogenetic model development and inference using PyTorch
https://github.com/AaltoML/BayesNewton
공식 코드Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
https://github.com/AaltoML/Newt
공식 코드https://github.com/AaltoML/kalman-jax
공식 코드State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
https://github.com/AaltoPML/machine-teaching-of-active-sequential-learners
공식 코드https://github.com/AdamCobb/hamiltorch
공식 코드https://github.com/AlexImmer/Laplace
공식 코드https://github.com/AlgoDynLab/SuperintelligenceTest
공식 코드https://github.com/Audio-WestlakeU/VINP
공식 코드https://github.com/AyakaSakata/GroupTesting
공식 코드Bayesian inference of infected patients in group testing with prevalence estimation
https://github.com/BEAST2-Dev/nested-sampling
공식 코드Model selection and parameter inference in phylogenetics using Nested Sampling
https://github.com/BIDData/BIDMach
공식 코드SAME but Different: Fast and High-Quality Gibbs Parameter Estimation
https://github.com/BayesWatch/deep-kernel-transfer
공식 코드Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels
https://github.com/BerkeleyLearnVerify/Scenic
공식 코드Scenic: A Language for Scenario Specification and Scene Generation
https://github.com/Berthaniu/LatentOptimalPathsBayesianDP
공식 코드Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming
https://github.com/BitSeq/BitSeqVB_benchmarking
공식 코드Fast and accurate approximate inference of transcript expression from RNA-seq data
https://github.com/Blei-Lab/lda-bump-cpp
공식 코드https://github.com/DPBayes/dca-nips2017
공식 코드Differentially Private Bayesian Learning on Distributed Data
https://github.com/DartML/Stein-Variational-Gradient-Descent
공식 코드Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
https://github.com/DeepWave-KAUST/AnnealedSVGD_FWI
공식 코드https://github.com/DiegoAE/BOSD
공식 코드https://github.com/DrugowitschLab/VBLinLogit
공식 코드Variational Bayesian inference for linear and logistic regression
https://github.com/EthanLan/BCNN
공식 코드Bayesian Convolutional Neural Networks for Compressed Sensing Restoration
https://github.com/ExtensityAI/symbolicai
공식 코드SymbolicAI: A framework for logic-based approaches combining generative models and solvers
https://github.com/GDMMBT/AcceleratedBradleyTerry
공식 코드Accelerated MM Algorithms for Ranking Scores Inference from Comparison Data
https://github.com/GFNOrg/gfn-lm-tuning
공식 코드https://github.com/Gongzhu-Society/MrIfOffline
공식 코드ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement Learning
https://github.com/HIPS/pgmult
공식 코드Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation
https://github.com/HarriBellThomas/VDQN
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.