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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/mp2893/mime

공식 코드

MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

https://github.com/mr-atharva-kulkarni/EACL-WASSA-2021-Empathy-Distress

공식 코드

PVG at WASSA 2021: A Multi-Input, Multi-Task, Transformer-Based Architecture for Empathy and Distress Prediction

https://github.com/mrjun123/DPETS

공식 코드

Practical Probabilistic Model-based Deep Reinforcement Learning by Integrating Dropout Uncertainty and Trajectory Sampling

https://github.com/mryansong/ccasgnn

공식 코드

CCasGNN: Collaborative Cascade Prediction Based on Graph Neural Networks

https://github.com/msesia/chr

공식 코드

Conformal Prediction using Conditional Histograms

https://github.com/msesia/cqr-comparison

공식 코드

A comparison of some conformal quantile regression methods

https://github.com/mswzeus/TargetNet

공식 코드

TargetNet: Functional microRNA Target Prediction with Deep Neural Networks

https://github.com/mufangying/informativeness-of-wcp

공식 코드

Informativeness of Weighted Conformal Prediction

https://github.com/muhanzhang/SEAL

공식 코드

Link Prediction Based on Graph Neural Networks

https://github.com/mulplue/mgf

공식 코드

MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction

https://github.com/mungomeng/deepmts

공식 코드

DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT

https://github.com/mungomeng/densepred-fullmlp

공식 코드

Full-resolution MLPs Empower Medical Dense Prediction

https://github.com/mungomeng/survival-adamss

공식 코드

AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images

https://github.com/mungomeng/survival-deepmss

공식 코드

AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images

https://github.com/mungomeng/survival-deepmts

공식 코드

DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT

https://github.com/mungomeng/survival-xsurv

공식 코드

Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer

https://github.com/mygit-yokoyamahiroshi/cd-rca_ijcnn2025

공식 코드

Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosis

https://github.com/mynlp/speechparser

공식 코드

Textless Dependency Parsing by Labeled Sequence Prediction

https://github.com/myxxxsquared/NLocalSAT

공식 코드

NLocalSAT: Boosting Local Search with Solution Prediction

https://github.com/mzaffran/conformalpredictionmissingvalues

공식 코드

Conformal Prediction with Missing Values

https://github.com/mzahana/drone_path_predictor_ros

공식 코드

VECTOR: Velocity-Enhanced GRU Neural Network for Real-Time 3D UAV Trajectory Prediction

https://github.com/naaclubert/ubert

공식 코드

UBERT: A Novel Language Model for Synonymy Prediction at Scale in the UMLS Metathesaurus

https://github.com/nachiket92/PGP

공식 코드

Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals

https://github.com/nachiket92/conv-social-pooling

공식 코드

Convolutional Social Pooling for Vehicle Trajectory Prediction

https://github.com/nadavlab/CPLLM

공식 코드

CPLLM: Clinical Prediction with Large Language Models

https://github.com/nadeemlab/cir

공식 코드

CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Radiomics and malignancy prediction

https://github.com/nandantumu/conformal_region_designer

공식 코드

Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates

https://github.com/nasosger/mutor

공식 코드

Multi-Token Prediction Needs Registers

https://github.com/naver-ai/fsmr

공식 코드

Feature Statistics Mixing Regularization for Generative Adversarial Networks

https://github.com/ndiamant/spice

공식 코드

Conformalized Deep Splines for Optimal and Efficient Prediction Sets

https://github.com/ndrwmlnk/ai-blitz-xiii

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Faces: AI Blitz XIII Solutions

https://github.com/ndrwmlnk/deep-face-generation-and-editing-a-survey

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Faces: AI Blitz XIII Solutions

https://github.com/needleworm/bigdata_voca

공식 코드

AI Knows Which Words Will Appear in Next Year's Korean CSAT

https://github.com/nehagianchandani/voxel-level-brain-age-prediction

공식 코드

A voxel-level approach to brain age prediction: A method to assess regional brain aging

https://github.com/neilzxu/active-rcps

공식 코드

Active, anytime-valid risk controlling prediction sets

https://github.com/neitzal/adaptive-skip-intervals

공식 코드

Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models

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