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/harvardnlp/sa-vae
https://github.com/henryaddison/score_sde_pytorch
https://github.com/hezhangsprinter/DID-MDN
Density-aware Single Image De-raining using a Multi-stream Dense Network
https://github.com/hojonathanho/localbitsback
https://github.com/horenbergerb/BernoulliDiffusion
https://github.com/hse-cs/probaforms
https://github.com/hungdhv97/Glow-Generative-Flow-with-Invertible-1x1-Convolutions
https://github.com/hyn2028/tpdm
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/ikostrikov/pytorch-flows
https://github.com/intuitive-robots/beso
Score-Based Generative Modeling through Stochastic Differential Equations
https://github.com/ispamm/realnvp-demo-pytorch
https://github.com/ivanvovk/WaveGrad
https://github.com/jackgoffinet/ffjord-lite
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
https://github.com/jcoreyes/ex2
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
https://github.com/jenyliu/DLA_interview
https://github.com/jeremyiv/diffc
https://github.com/jfcrenshaw/pzflow
https://github.com/jhjacobsen/invertible-resnet
https://github.com/jjunak-yun/FLowHigh_code
https://github.com/joh-fischer/PlantLDM
https://github.com/johnpjust/nsf
https://github.com/joshuacnf/Probabilistic-Generating-Circuits
https://github.com/jtamanas/mssm
Fully probabilistic quasar continua predictions near Lyman-α with conditional neural spline flows
https://github.com/judonini/DarkMachines
https://github.com/jurgisp/pydreamer
https://github.com/kamenbliznashki/pixel_models
https://github.com/kampta/pytorch-distributions
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
https://github.com/karlnapf/kernel_exp_family
Density Estimation in Infinite Dimensional Exponential Families
https://github.com/karpathy/pytorch-made
https://github.com/kbountro/cSAX
https://github.com/keonlee9420/DiffGAN-TTS
https://github.com/keonlee9420/DiffSinger
https://github.com/keonlee9420/VAENAR-TTS
https://github.com/kevindeangeli/capsuleNetwork
Fast Dynamic Routing Based on Weighted Kernel Density Estimation
https://github.com/khalil-research/pyepo
Backpropagation through Combinatorial Algorithms: Identity with Projection Works
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.