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Density Estimation

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하위 태스크: 1
평가표: 14
보존된 평가 기록: 65

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/kabolat/leave-one-out_maximum-log-likelihood

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Stable Training of Probabilistic Models Using the Leave-One-Out Maximum Log-Likelihood Objective

https://github.com/karlnapf/kernel_goodness_of_fit

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A Kernel Test of Goodness of Fit

https://github.com/karlnapf/nystrom-kexpfam

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Efficient and principled score estimation with Nyström kernel exponential families

https://github.com/karokaram/PrivatedBoostedDensities

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Integral Privacy for Sampling

https://github.com/kbountro/pSAX

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Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly Detection

https://github.com/khainb/sbnpm-sot

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Summarizing Bayesian Nonparametric Mixture Posterior -- Sliced Optimal Transport Metrics for Gaussian Mixtures

https://github.com/kimmo1019/Roundtrip

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Roundtrip: A Deep Generative Neural Density Estimator

https://github.com/konstantinklemmer/pe-gnn

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Positional Encoder Graph Quantile Neural Networks for Geographic Data

https://github.com/kosieram21/trajflow

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TrajFlow: A Generative Framework for Occupancy Density Estimation Using Normalizing Flows

https://github.com/kulinshah98/overparam-nfs

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Learning and Generalization in Overparameterized Normalizing Flows

https://github.com/lagergren-lab/miselbo

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Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations

https://github.com/lagergren-lab/vaiphy

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VaiPhy: a Variational Inference Based Algorithm for Phylogeny

https://github.com/lagergren-lab/vbpi-mixtures

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Improved Variational Bayesian Phylogenetic Inference using Mixtures

https://github.com/lamda-bbo/sbokde

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Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation

https://github.com/larajuse/DMAE

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Dissimilarity Mixture Autoencoder for Deep Clustering

https://github.com/laurarkart/Physical-Anomalous-Trajectory-or-Motion-PHANTOM-Dataset

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Approaches Toward Physical and General Video Anomaly Detection

https://github.com/layer6ai-labs/CEF

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Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows

https://github.com/layer6ai-labs/calo-man

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CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds

https://github.com/layer6ai-labs/implicit-manifolds

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Neural Implicit Manifold Learning for Topology-Aware Density Estimation

https://github.com/layer6ai-labs/rectangular-flows

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Rectangular Flows for Manifold Learning

https://github.com/layer6ai-labs/two_step_zoo

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Diagnosing and Fixing Manifold Overfitting in Deep Generative Models

https://github.com/lee-group-cmu/cal-pit

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Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)

https://github.com/lelouedec/phd_3dperception

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Gaussian map predictions for 3D surface feature localisation and counting

https://github.com/li012589/neuralCT

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Neural Canonical Transformation with Symplectic Flows

https://github.com/lihenryhfl/nits

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Neural Inverse Transform Sampler

https://github.com/lihenryhfl/pcdm

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Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps

https://github.com/lixilinx/TriNet4PdfEst

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A Triangular Network For Density Estimation

https://github.com/lliutianc/gan-flow

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An Empirical Comparison of GANs and Normalizing Flows for Density Estimation

https://github.com/lminvielle/mom-kde

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Robust Kernel Density Estimation with Median-of-Means principle

https://github.com/louis-pujol/isde-paper

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ISDE : Independence Structure Density Estimation

https://github.com/lupalab/ace

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Arbitrary Conditional Distributions with Energy

https://github.com/lupalab/flowscan

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Exchangeable Generative Models with Flow Scans

https://github.com/lupalab/posterior-matching

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Posterior Matching for Arbitrary Conditioning

https://github.com/majid-daliri/kdeformer

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KDEformer: Accelerating Transformers via Kernel Density Estimation

https://github.com/marclafon/heatood

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Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection

https://github.com/marco-rudolph/ast

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Asymmetric Student-Teacher Networks for Industrial Anomaly Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.