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Prediction

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

https://github.com/hkashyap/SparseMotion

공식 코드

Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes

https://github.com/hkmztrk/DeepDTA

공식 코드

DeepDTA: Deep Drug-Target Binding Affinity Prediction

https://github.com/hkuds/easyst

공식 코드

EasyST: A Simple Framework for Spatio-Temporal Prediction

https://github.com/hkuds/flashst

공식 코드

FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction

https://github.com/hkuds/opencity

공식 코드

OpenCity: Open Spatio-Temporal Foundation Models for Traffic Prediction

https://github.com/hkunlp/rsa

공식 코드

Retrieved Sequence Augmentation for Protein Representation Learning

https://github.com/hkust-nisl/oat_eccv24

공식 코드

OAT: Object-Level Attention Transformer for Gaze Scanpath Prediction

https://github.com/hoangminhle/SIMILE

공식 코드

Smooth Imitation Learning for Online Sequence Prediction

https://github.com/hong-yu-zhang/omniesi

공식 코드

OmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning

https://github.com/hongbo-z/snna

공식 코드

Noise-Free Explanation for Driving Action Prediction

https://github.com/hongklin/tide

공식 코드

A Unified Image-Dense Annotation Generation Model for Underwater Scenes

https://github.com/hongnianwang/STAR

공식 코드

STAR: A Concise Deep Learning Framework for Citywide Human Mobility Prediction

https://github.com/hongshuh/matinformer

공식 코드

Materials Informatics Transformer: A Language Model for Interpretable Materials Properties Prediction

https://github.com/hongsong-wang/PVRNN

공식 코드

PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction

https://github.com/hongxiaoy/ISO

공식 코드

Monocular Occupancy Prediction for Scalable Indoor Scenes

https://github.com/hprcest/lfpbench

공식 코드

Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction

https://github.com/hrlics/lite

공식 코드

LITE: Modeling Environmental Ecosystems with Multimodal Large Language Models

https://github.com/hrtavakoli/DAVE

공식 코드

DAVE: A Deep Audio-Visual Embedding for Dynamic Saliency Prediction

https://github.com/hs-yn/daps

공식 코드

Dense 2D-3D Indoor Prediction with Sound via Aligned Cross-Modal Distillation

https://github.com/hsaest/quert

공식 코드

QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search

https://github.com/hsd1503/HOLMES

공식 코드

HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units

https://github.com/hsianghsu/fair-projection

공식 코드

Beyond Adult and COMPAS: Fairness in Multi-Class Prediction

https://github.com/hsliu-initial/rok

공식 코드

Retrieval-Oriented Knowledge for Click-Through Rate Prediction

https://github.com/hsy23/kdd23_dyneformer

공식 코드

One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms

https://github.com/huage001/painttransformer

공식 코드

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

https://github.com/huang-yh/selfocc

공식 코드

SelfOcc: Self-Supervised Vision-Based 3D Occupancy Prediction

https://github.com/huawei-noah/SMARTS

공식 코드

CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous Driving

https://github.com/huawei-noah/benchmark

공식 코드

TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction

https://github.com/huaxiuyao/DMVST-Net

공식 코드

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

https://github.com/huaxiuyao/MetaST

공식 코드

Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction

https://github.com/huiyu-2002/ifactformer-m

공식 코드

Implicit factorized transformer approach to fast prediction of turbulent channel flows

https://github.com/humphreyhuu/dualk

공식 코드

Bridging Stepwise Lab-Informed Pretraining and Knowledge-Guided Learning for Diagnostic Reasoning

https://github.com/hworang77/PAN

공식 코드

Progressive Attention Networks for Visual Attribute Prediction

https://github.com/hxstarklin/DSAN

공식 코드

Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction

https://github.com/hyf015/egocentric-gaze-prediction

공식 코드

Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition

https://github.com/hyperconnect/LADE

공식 코드

Disentangling Label Distribution for Long-tailed Visual Recognition

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