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://github.com/oxcsaml2019/multitask-learning

Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics

https://github.com/oylz/FDSSTTest

High-Speed Tracking with Kernelized Correlation Filters

https://github.com/panditanvita/BTCpredictor

Bayesian regression and Bitcoin

https://github.com/pangshumao/CARN

Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network

https://github.com/paplhjak/facial-age-estimation-benchmark

Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression

https://github.com/parikhs97/Predicting-Bitcoin-Price-Variations

Bayesian regression and Bitcoin

https://github.com/pat-s/paper_hyperspectral

SPSA-FSR: Simultaneous Perturbation Stochastic Approximation for Feature Selection and Ranking

https://github.com/patel-zeel/coreset

Practical Coreset Constructions for Machine Learning

https://github.com/patrikhuber/superviseddescent

Fitting 3D Morphable Models using Local Features

https://github.com/pchlenski/embedders

Mixed-curvature decision trees and random forests

https://github.com/pedrobvidal/insightface

Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression

https://github.com/peisuke/awr

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

https://github.com/perrin-isir/afu

Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization

https://github.com/piEsposito/blitz-bayesian-deep-learning

Weight Uncertainty in Neural Networks

https://github.com/pihey1995/DistributionalRL

Implicit Quantile Networks for Distributional Reinforcement Learning

https://github.com/pinouche/attention-MIR

Learning with Sets in Multiple Instance Regression Applied to Remote Sensing

https://github.com/pkuyym/evolvingattention

A Transformer-based Framework for Multivariate Time Series Representation Learning

https://github.com/plai-group/ccfs-python

Canonical Correlation Forests

https://github.com/pmorerio/dl-uncertainty

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

https://github.com/pmshst/A-Real-time-System-of-Bitcoin-Price-Prediction

Bayesian regression and Bitcoin

https://github.com/potsawee/maml

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/ppengtang/pcl.pytorch

Towards Precise End-to-end Weakly Supervised Object Detection Network

https://github.com/prajjwal1/fluence

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/predict-idlab/landmarker

Integrating Spatial Configuration into Heatmap Regression Based CNNs for Landmark Localization

https://github.com/prmody96/Predicting-Bitcoin-Price-Variations-using-Bayesian-Regression

Bayesian regression and Bitcoin

https://github.com/psejenks/berkeley_u20

A Statistical Comparison of Some Theories of NP Word Order

https://github.com/psh150204/MAML

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/ptran1203/facial_beauty

SCUT-FBP5500: A Diverse Benchmark Dataset for Multi-Paradigm Facial Beauty Prediction

https://github.com/py-econometrics/duckreg

Fixed Effects and the Generalized Mundlak Estimator

https://github.com/pycroscopy/atomai

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

https://github.com/pyro-ppl/pyro

Doubly Stochastic Variational Inference for Deep Gaussian Processes

https://github.com/radhen/BebionicFingerSensor

Real-time regression analysis with deep convolutional neural networks

https://github.com/rahulkidambi/AccSGD

Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification

https://github.com/rahulmaz/L0BnB

Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization

https://github.com/rajatdge/Bitcoin-Price-Prediction

Bayesian regression and Bitcoin

https://github.com/rajkumarkarthik/mgrf-develop

Generalized Random Forests

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