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Prediction

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코드

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

https://github.com/vekteur/multi-output-conformal-regression

공식 코드

A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression

https://github.com/vencent-won/sggrl

공식 코드

Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry

https://github.com/venomouscyanide/s3grl

공식 코드

Simplifying Subgraph Representation Learning for Scalable Link Prediction

https://github.com/venomouscyanide/s3grl_ogb

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Simplifying Subgraph Representation Learning for Scalable Link Prediction

https://github.com/venomouscyanide/scaled

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Sampling Enclosing Subgraphs for Link Prediction

https://github.com/verdurechen/group-qpp

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Groupwise Query Performance Prediction with BERT

https://github.com/vertaix/llm4mat-bench

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LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction

https://github.com/vico-uoe/mtpsl

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Learning Multiple Dense Prediction Tasks from Partially Annotated Data

https://github.com/victorchan314/arterial_traffic_flow_predictor

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A Graph Convolutional Network with Signal Phasing Information for Arterial Traffic Prediction

https://github.com/viewsetting/unsupervised_sampling_promoting

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Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction

https://github.com/vijulshah/webcam-based-pupil-diameter-estimation

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Webcam-based Pupil Diameter Prediction Benefits from Upscaling

https://github.com/vikranth3140/movie-revenue-prediction

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Movie Revenue Prediction using Machine Learning Models

https://github.com/viktorvdvalk/task-specific-vae

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Joint optimization of a $β$-VAE for ECG task-specific feature extraction

https://github.com/vimal-isi-edu/vdp-emc

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A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment

https://github.com/vincent-1125/uncertainty-quantification-on-clinical-trial-outcome-prediction

공식 코드

Uncertainty Quantification on Clinical Trial Outcome Prediction

https://github.com/vincent-leguen/PhyDNet

공식 코드

Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction

https://github.com/vincentblot28/conformalized_gp

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Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees

https://github.com/vineetjohn/linguistic-style-transfer

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Disentangled Representation Learning for Non-Parallel Text Style Transfer

https://github.com/visionml/pytracking

공식 코드

Learning Discriminative Model Prediction for Tracking

https://github.com/vita-epfl/SVGNet

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SVG-Net: An SVG-based Trajectory Prediction Model

https://github.com/vita-epfl/bounding-box-prediction

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Pedestrian Intention Prediction: A Multi-task Perspective

https://github.com/vita-epfl/deposit

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A generic diffusion-based approach for 3D human pose prediction in the wild

https://github.com/vita-epfl/monotransmotion

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Unified Human Localization and Trajectory Prediction with Monocular Vision

https://github.com/vita-epfl/multi-transmotion

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Multi-Transmotion: Pre-trained Model for Human Motion Prediction

https://github.com/vita-epfl/social-transmotion

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Social-Transmotion: Promptable Human Trajectory Prediction

https://github.com/vita-epfl/stay-on-track

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A Multi-Loss Strategy for Vehicle Trajectory Prediction: Combining Off-Road, Diversity, and Directional Consistency Losses

https://github.com/vita-epfl/unitraj

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UniTraj: A Unified Framework for Scalable Vehicle Trajectory Prediction

https://github.com/voletiv/mcvd-pytorch

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MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation

https://github.com/vperifan/federated-time-series-forecasting

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Towards Energy-Aware Federated Traffic Prediction for Cellular Networks

https://github.com/vshy-dream/drexplainer

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DRExplainer: Quantifiable Interpretability in Drug Response Prediction with Directed Graph Convolutional Network

https://github.com/vtp-tl/d2-tpred

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D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights

https://github.com/vunhatminh/PGMExplainer

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PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks

https://github.com/vuptran/graph-representation-learning

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Learning to Make Predictions on Graphs with Autoencoders

https://github.com/vwz/topolstm

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Topological Recurrent Neural Network for Diffusion Prediction

https://github.com/wahlby-lab/InSilicoTFM

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In Silico Prediction of Cell Traction Forces

https://github.com/walking-shadow/Official_Remote_Sensing_Mamba

공식 코드

RS-Mamba for Large Remote Sensing Image Dense Prediction

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