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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/mhamilton723/FeatUp

공식 코드

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

https://github.com/mhassandev/ShoeNet

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Deep Learning Analysis and Age Prediction from Shoeprints

https://github.com/mhrnz/performative-prediction-with-neural-networks

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Performative Prediction with Neural Networks

https://github.com/mhsamavatian/DAP

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Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights

https://github.com/mhtang1995/bopn

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A Boundary Offset Prediction Network for Named Entity Recognition

https://github.com/mhtang1995/cppt

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Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning

https://github.com/mi-biolab/region-learner

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Region Prediction for Efficient Robot Localization on Large Maps

https://github.com/mi2datalab/limecraft

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LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations

https://github.com/mi2datalab/survshap

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SurvSHAP(t): Time-dependent explanations of machine learning survival models

https://github.com/michaelyuancb/general_flow

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General Flow as Foundation Affordance for Scalable Robot Learning

https://github.com/michalzajac-ml/pec

공식 코드

Prediction Error-based Classification for Class-Incremental Learning

https://github.com/michigan-traffic-lab/DECODE

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DECODE: Domain-aware Continual Domain Expansion for Motion Prediction

https://github.com/microsoft/CryptoNets

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Crypto-Nets: Neural Networks over Encrypted Data

https://github.com/microsoft/ProphetNet

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ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training

https://github.com/microsoft/caspr

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CASPR: Customer Activity Sequence-based Prediction and Representation

https://github.com/microsoft/comphrdoc

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UniHDSA: A Unified Relation Prediction Approach for Hierarchical Document Structure Analysis

https://github.com/microsoft/healthcareai-examples

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Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model Representations

https://github.com/microsoft/horseshoe-bnn

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Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care

https://github.com/microsoft/sphnet

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Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity

https://github.com/mie-lab/geospatial_optimal_transport

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GeOT: A spatially explicit framework for evaluating spatio-temporal predictions

https://github.com/mie-lab/geospatialot

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GeOT: A spatially explicit framework for evaluating spatio-temporal predictions

https://github.com/mie-lab/location-mode-prediction

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How do you go where? Improving next location prediction by learning travel mode information using transformers

https://github.com/mie-lab/location-prediction

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Context-aware multi-head self-attentional neural network model for next location prediction

https://github.com/miguelag99/efficient-instance-prediction

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Fast and Efficient Transformer-based Method for Bird's Eye View Instance Prediction

https://github.com/mindspore-ai/mindscience/tree/master/MindSPONGE/applications/MEGAProtein

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PSP: Million-level Protein Sequence Dataset for Protein Structure Prediction

https://github.com/mingchenli/VGAE_Attack_Meta

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Exploiting Meta-Learning-based Poisoning Attacks for Graph Link Prediction

https://github.com/minghanz/DepthC3D

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Monocular Depth Prediction through Continuous 3D Loss

https://github.com/minghanz/c3d

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Monocular Depth Prediction through Continuous 3D Loss

https://github.com/mingmtc/hdr

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Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach

https://github.com/mingxilii/localegn

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Few-Sample Traffic Prediction with Graph Networks using Locale as Relational Inductive Biases

https://github.com/mingyue-cheng/hmf

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A Hybrid Multi-Factor Network with Dynamic Sequence Modeling for Early Warning of Intraoperative Hypotension

https://github.com/minh1409/dft-npzs-nas

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Efficacy of Neural Prediction-Based Zero-Shot NAS

https://github.com/minhnhat93/mpc-bounded-regret-evaluation

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Empirical Study of Dynamic Regret in Online Model Predictive Control for Linear Time-Varying Systems

https://github.com/minoru938/cspml

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Crystal structure prediction with machine learning-based element substitution

https://github.com/mipt-oulu/oaprogressionmr

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Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning

https://github.com/mit-han-lab/efficientvit

공식 코드

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

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