Papers with Code 아카이브
Density Estimation
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The goal of Density Estimation is to give an accurate description of the underlying probabilistic density distribution of an observable data set with unknown density.
Source: Contrastive Predictive Coding Based Feature for Automatic Speaker Verification
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/y0ast/Glow-PyTorch
https://github.com/yanfeng-yang-0316/cdcit
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/yang-song/score_inverse_problems
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/yang-song/score_sde_pytorch
https://github.com/yaoli/nade_k
Iterative Neural Autoregressive Distribution Estimator (NADE-k)
https://github.com/yburda/iwae
https://github.com/yiyixuxu/denoising-diffusion-flax
https://github.com/yoojy31/mixture-density-object-detector
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image
https://github.com/youtang1993/mixture-model-based-object-detector
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image
https://github.com/yoyololicon/variational-diffwave
https://github.com/yqtianust/Awesome-SE-for-AI
APRICOT: A Dataset of Physical Adversarial Attacks on Object Detection
https://github.com/yschroecker/universal_value_density_estimation
https://github.com/zhangsilu17/Gini_distance_statistics
Estimating Feature-Label Dependence Using Gini Distance Statistics
https://github.com/zhaokg/rbeast
https://github.com/zhoudoao-bayes/tf-probability
https://github.com/zonems/enko
https://gitlab.com/i-flow/i-flow
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.