Papers with Code 아카이브

regression

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

2

평가표

6

보존된 평가 기록

15

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/A_2/hcup_research

공식 코드

Neural networks versus Logistic regression for 30 days all-cause readmission prediction

https://bitbucket.org/aicip/face-aging-caae

공식 코드

Age Progression/Regression by Conditional Adversarial Autoencoder

https://bitbucket.org/gsudmlab/ensemble_fp/src/main/revised_expt/

공식 코드

Towards Coupling Full-disk and Active Region-based Flare Prediction for Operational Space Weather Forecasting

https://bitbucket.org/jhhuggins/lrcoresets

공식 코드

Coresets for Scalable Bayesian Logistic Regression

https://bitbucket.org/jhhuggins/pass-glm

공식 코드

PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference

https://bitbucket.org/mpratola/openbt

공식 코드

Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models

https://bitbucket.org/mvdschaar/mlforhealthlabpub

공식 코드

Learning Overlapping Representations for the Estimation of Individualized Treatment Effects

https://bitbucket.org/nathanhuet/extremeregression

공식 코드

On Regression in Extreme Regions

https://bitbucket.org/params/dsmlr

공식 코드

DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression

https://bitbucket.org/sahasuman/bmvc2016_code

공식 코드

Online Spatiotemporal Action Detection and Prediction via Causal Representations

https://bitbucket.org/szzoli/ite

공식 코드

Learning Theory for Distribution Regression

https://bitbucket.org/uwtppml/idash2019

공식 코드

High Performance Logistic Regression for Privacy-Preserving Genome Analysis

https://cran.r-project.org/web/packages/dual.spls

공식 코드

Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection and prediction with tunable sparsity; evaluation on simulated and near-infrared (NIR) data

https://git.opendfki.de/koochali/forgan

공식 코드

Probabilistic Forecasting of Sensory Data with Generative Adversarial Networks - ForGAN

https://git.uwaterloo.ca/data-analytics-lab/symbolicgpt2

공식 코드

SymbolicGPT: A Generative Transformer Model for Symbolic Regression

https://gitee.com/xiaoyibang/clipdrug

공식 코드

CLDR: Contrastive Learning Drug Response Models from Natural Language Supervision

https://github.com/000Justin000/gnn-residual-correlation

공식 코드

Residual Correlation in Graph Neural Network Regression

https://github.com/0731steven/anru-zhang

공식 코드

Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay

https://github.com/0v/esim-ad

공식 코드

Event-based Camera Simulation using Monte Carlo Path Tracing with Adaptive Denoising

https://github.com/11301858/xaisuite

공식 코드

The XAISuite framework and the implications of explanatory system dissonance

https://github.com/1716757342/metsymnet

공식 코드

MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions

https://github.com/1716757342/mmsr

공식 코드

MMSR: Symbolic Regression is a Multi-Modal Information Fusion Task

https://github.com/1adrianb/face-alignment

공식 코드

Two-stage Convolutional Part Heatmap Regression for the 1st 3D Face Alignment in the Wild (3DFAW) Challenge

https://github.com/1adrianb/human-pose-estimation

공식 코드

Human pose estimation via Convolutional Part Heatmap Regression

https://github.com/2geeks2/labelawareranked-loss

공식 코드

Label-Aware Ranked Loss for robust People Counting using Automotive in-cabin Radar

https://github.com/3DVisionISR/3DRegNet

공식 코드

3DRegNet: A Deep Neural Network for 3D Point Registration

https://github.com/4flixt/2022_paper_bll_lml

공식 코드

Improved uncertainty quantification for neural networks with Bayesian last layer

https://github.com/4flixt/2023_paper_bll_lml

공식 코드

Improved uncertainty quantification for neural networks with Bayesian last layer

https://github.com/775269512/sigspatial-2021-giscup-4th-solution

공식 코드

Multi View Spatial-Temporal Model for Travel Time Estimation

https://github.com/AFAgarap/wisconsin-breast-cancer

공식 코드

On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

https://github.com/AI-secure/GMI-Attack

공식 코드

The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks

https://github.com/AIgen/QOOB

공식 코드

Nested conformal prediction and quantile out-of-bag ensemble methods

https://github.com/ASTAugustin/ICML_WNTK

공식 코드

Weighted Neural Tangent Kernel: A Generalized and Improved Network-Induced Kernel

https://github.com/AaltoML/boundary-gp

공식 코드

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

https://github.com/AaltoML/hilbert-gp

공식 코드

Hilbert Space Methods for Reduced-Rank Gaussian Process Regression

https://github.com/AaronJackson/vrn

공식 코드

Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression

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