Papers with Code 아카이브

regression

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하위 태스크

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평가표

6

보존된 평가 기록

15

코드

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

https://github.com/zengwang430521/DecoMR

공식 코드

3D Human Mesh Regression with Dense Correspondence

https://github.com/zgbkdlm/dissertation

공식 코드

State-space deep Gaussian processes with applications

https://github.com/zgbkdlm/ssdgp

공식 코드

Deep State-Space Gaussian Processes

https://github.com/zgspose/dsta

공식 코드

Video-Based Human Pose Regression via Decoupled Space-Time Aggregation

https://github.com/zhan-gao/LasForecast

공식 코드

Econometric Inference for High Dimensional Predictive Regressions

https://github.com/zhangsj96/pgnets

공식 코드

PGNets: Planet mass prediction using convolutional neural networks for radio continuum observations of protoplanetary disks

https://github.com/zhaochangming/boostforest

공식 코드

BoostTree and BoostForest for Ensemble Learning

https://github.com/zhaoyuzhi/Hierarchical-Regression-Network-for-Spectral-Reconstruction-from-RGB-Images

공식 코드

Hierarchical Regression Network for Spectral Reconstruction from RGB Images

https://github.com/zhehengjianglancaster/amvur

공식 코드

A Probabilistic Attention Model with Occlusion-aware Texture Regression for 3D Hand Reconstruction from a Single RGB Image

https://github.com/zhengchen1999/hi-diff

공식 코드

Hierarchical Integration Diffusion Model for Realistic Image Deblurring

https://github.com/zhentaoshi/panel-local-projection

공식 코드

Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You Think

https://github.com/zhiqic/keyposs

공식 코드

KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration

https://github.com/zhonglifr/qcad

공식 코드

Explainable Contextual Anomaly Detection using Quantile Regression Forests

https://github.com/zhou13/nerd

공식 코드

NeRD: Neural 3D Reflection Symmetry Detector

https://github.com/zhouc20/latentgraphdiffusion

공식 코드

Unifying Generation and Prediction on Graphs with Latent Graph Diffusion

https://github.com/zhoufeng6288/hgcox

공식 코드

Heterogeneous Multi-Task Gaussian Cox Processes

https://github.com/zhoutianxun/data_free_kd_regression

공식 코드

Synthetic data generation method for data-free knowledge distillation in regression neural networks

https://github.com/zhu-xlab/htc-dc-net

공식 코드

HTC-DC Net: Monocular Height Estimation from Single Remote Sensing Images

https://github.com/zhuxing0/SR-Stereov1-DAPE

공식 코드

SR-Stereo & DAPE: Stepwise Regression and Pre-trained Edges for Practical Stereo Matching

https://github.com/zhyever/monocular-depth-estimation-toolbox

공식 코드

BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation

https://github.com/zhyuan11/SPE

공식 코드

Learning High-Frequency Functions Made Easy with Sinusoidal Positional Encoding

https://github.com/zijunli7/condo

공식 코드

ConDo: Continual Domain Expansion for Absolute Pose Regression

https://github.com/zim10/determine_toxic_comment_and_identity_bias

공식 코드

Determination of toxic comments and unintended model bias minimization using Deep learning approach

https://github.com/zinka88/Fair-Regression

공식 코드

Fair Regression for Health Care Spending

https://github.com/ziqian2000/smiling

공식 코드

Diffusing States and Matching Scores: A New Framework for Imitation Learning

https://github.com/ziqin-h/givepose

공식 코드

GIVEPose: Gradual Intra-class Variation Elimination for RGB-based Category-Level Object Pose Estimation

https://github.com/zjumai/dfpg-ord

공식 코드

Dual-level Fuzzy Learning with Patch Guidance for Image Ordinal Regression

https://github.com/zleizzo/ddgroup

공식 코드

Data-Driven Subgroup Identification for Linear Regression

https://github.com/zlin7/cptd

공식 코드

Conformal Prediction Intervals with Temporal Dependence

https://github.com/zqs01/data2vecnoisy

공식 코드

Robust Data2vec: Noise-robust Speech Representation Learning for ASR by Combining Regression and Improved Contrastive Learning

https://github.com/zuowx/deeplink-t

공식 코드

DeepLINK-T: deep learning inference for time series data using knockoffs and LSTM

https://github.com/zurichnlp/recognizing-semantic-differences

공식 코드

Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents

https://github.com/zwd-ms/risk_averse_cb

공식 코드

Conditionally Risk-Averse Contextual Bandits

https://github.com/zwh0527/lgfctr

공식 코드

LGFCTR: Local and Global Feature Convolutional Transformer for Image Matching

https://github.com/zxhuang1698/ZeroShape

공식 코드

ZeroShape: Regression-based Zero-shot Shape Reconstruction

https://github.com/zykhoo/ai-feynman

공식 코드

Celestial Machine Learning: From Data to Mars and Beyond with AI Feynman

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