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/vietanhdev/tf-blazepose

BlazePose: On-device Real-time Body Pose tracking

https://github.com/vision4robotics/DR2Track/tree/master/DR2Track1

DR^2Track: Towards Real-Time Visual Tracking for UAV via Distractor Repressed Dynamic Regression

https://github.com/vittorioorlandi/drbart

BART: Bayesian additive regression trees

https://github.com/vladmandic/blazepose

BlazePose: On-device Real-time Body Pose tracking

https://github.com/vr308/Generalised-Gaussian-Processes

Approximate Inference for Fully Bayesian Gaussian Process Regression

https://github.com/vshirvaikar/rrcf

Generalized Random Forests

https://github.com/vsomnath/holoprot

Multi-Scale Representation Learning on Proteins

https://github.com/vub-ai-lab/qwr

Q-Value Weighted Regression: Reinforcement Learning with Limited Data

https://github.com/vuthede/heatmap-based-landmarker

Heatmap Regression via Randomized Rounding

https://github.com/vvanirudh/deep-ensembles-uncertainty

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

https://github.com/w-sugar/prtr

Pose Recognition with Cascade Transformers

https://github.com/wanboyang/Anomaly_AR_Net_ICME_2020

Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning

https://github.com/wangermeng2021/Scaled-YOLOv4-tensorflow2

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

https://github.com/wangzt-halo/das

Distribution-Aware Single-Stage Models for Multi-Person 3D Pose Estimation

https://github.com/wayoo2019/DSC440-Data-Mining

US Fatal Police Shooting Analysis and Prediction

https://github.com/weiwang2330/sparse-structured-attention

The Ordered Weighted $\ell_1$ Norm: Atomic Formulation, Projections, and Algorithms

https://github.com/wesselb/plum

The Gaussian Process Autoregressive Regression Model (GPAR)

https://github.com/wsx66848/tsd

Revisiting the Sibling Head in Object Detector

https://github.com/wtong98/equality-reasoning

MLPs Learn In-Context on Regression and Classification Tasks

https://github.com/wujian16/qKG

A Tutorial on Bayesian Optimization

https://github.com/wwooo/tensorflow_complex_yolo

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

https://github.com/wyn430/NP_ODE

Attentive Neural Processes

https://github.com/xbpeng/awr

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

https://github.com/xialeiliu/RankIQA

Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank

https://github.com/xiaobai1217/MBMD

Learning regression and verification networks for long-term visual tracking

https://github.com/xiaoling2yy/Bounding-Box-Regression-with-Uncertainty-for-Accurate-Object-Detection

Bounding Box Regression with Uncertainty for Accurate Object Detection

https://github.com/xiuyu0000/new_papers_codes/tree/main/DecoMR

3D Human Mesh Regression with Dense Correspondence

https://github.com/xiuyu0000/new_papers_codes/tree/main/MAML

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

https://github.com/xiuyu0000/new_papers_codes/tree/main/cmr

Convolutional Mesh Regression for Single-Image Human Shape Reconstruction

https://github.com/xmu-xiaoma666/External-Attention-pytorch/blob/master/attention/PolarizedSelfAttention.py

Polarized Self-Attention: Towards High-quality Pixel-wise Regression

https://github.com/xrndai/DeepDayTrade

Neural networks for stock price prediction

https://github.com/xuduo35/STAPLE

Staple: Complementary Learners for Real-Time Tracking

https://github.com/xue-pai/FuxiCTR

Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks

https://github.com/xuyxu/Ensemble-Pytorch

Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

https://github.com/yang1fan2/Dota2-Prediction

Real-time eSports Match Result Prediction

https://github.com/yanggeng1995/WaveGlow

WaveGlow: A Flow-based Generative Network for Speech Synthesis

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