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Model Optimization

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To Optimize already existing models in Training/Inferencing tasks.

코드

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

https://github.com/41enthusiast/ST-SACLF-ver1.1

공식 코드

ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification

https://github.com/4real3000/easyjudge

공식 코드

EasyJudge: an Easy-to-use Tool for Comprehensive Response Evaluation of LLMs

https://github.com/CharlieDinh/pFedMe

공식 코드

Personalized Federated Learning with Moreau Envelopes

https://github.com/Chenglu0426/FairGraphFL

공식 코드

Towards Fair Graph Federated Learning via Incentive Mechanisms

https://github.com/DSC-SPIDAL/rankpredictor

공식 코드

Rank Position Forecasting in Car Racing

https://github.com/Jeckinchen/PhyCoBench

공식 코드

A Physical Coherence Benchmark for Evaluating Video Generation Models via Optical Flow-guided Frame Prediction

https://github.com/KU-CVLAB/INR-st

공식 코드

Controllable Style Transfer via Test-time Training of Implicit Neural Representation

https://github.com/Lee-Gihun/FedSOL

공식 코드

FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning

https://github.com/MJ10/DEUP

공식 코드

DEUP: Direct Epistemic Uncertainty Prediction

https://github.com/MhLiao/DB

공식 코드

Real-Time Scene Text Detection with Differentiable Binarization and Adaptive Scale Fusion

https://github.com/NVlabs/FedFomo

공식 코드

Personalized Federated Learning with First Order Model Optimization

https://github.com/PerdonLiu/CSE-Autoloss

공식 코드

Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search

https://github.com/RuiZhang2016/Variational-Inference-for-SGP-Modulated-Hawkes-Process

공식 코드

Variational Inference for Sparse Gaussian Process Modulated Hawkes Process

https://github.com/SeyedMuhammadHosseinMousavi/Victoria-Amazonica-Optimization-VAO-Algorithm

공식 코드

Victoria Amazonica Optimization (VAO): An Algorithm Inspired by the Giant Water Lily Plant

https://github.com/TaehwanY98/Fed-Ref

공식 코드

FedRef: Communication-Efficient Bayesian Fine Tuning with Reference Model

https://github.com/USTCAGI/Awesome-Cross-Domain-Recommendation-Papers-and-Resources

공식 코드

A Comprehensive Survey on Cross-Domain Recommendation: Taxonomy, Progress, and Prospects

https://github.com/WisdomShell/RewardAnything

공식 코드

RewardAnything: Generalizable Principle-Following Reward Models

https://github.com/Yruikk/MUSO

공식 코드

MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes

https://github.com/alchemyemperor/siavc

공식 코드

SIAVC: Semi-Supervised Framework for Industrial Accident Video Classification

https://github.com/alfurka/synloc

공식 코드

Generating Synthetic Data with Locally Estimated Distributions for Disclosure Control

https://github.com/algohunt/streamrf

공식 코드

Streaming Radiance Fields for 3D Video Synthesis

https://github.com/allenai/cartography

공식 코드

Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics

https://github.com/anibalsilva1/irmodeloptimization

공식 코드

Model Optimization in Imbalanced Regression

https://github.com/applied-machine-learning-lab/awesome-multimodal-recommender-systems

공식 코드

Multimodal Recommender Systems: A Survey

https://github.com/aristotelisballas/gga

공식 코드

Gradient-Guided Annealing for Domain Generalization

https://github.com/baiyimeng/labelcraft

공식 코드

LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting

https://github.com/bharathsudharsan/cnn_on_mcu

공식 코드

Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware

https://github.com/bruno686/dcf

공식 코드

Double Correction Framework for Denoising Recommendation

https://github.com/bytedance/pargo

공식 코드

MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

https://github.com/charliebtan/fractal_dimensions

공식 코드

On the Limitations of Fractal Dimension as a Measure of Generalization

https://github.com/chenhu96/self-supervised-mri-reconstruction

공식 코드

Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework

https://github.com/compostieai/guava-disease-detection

공식 코드

Device-friendly Guava fruit and leaf disease detection using deep learning

https://github.com/dearcaat/pict

공식 코드

PicT: A Slim Weakly Supervised Vision Transformer for Pavement Distress Classification

https://github.com/dk-liang/AutoScale

공식 코드

AutoScale: Learning to Scale for Crowd Counting and Localization

https://github.com/dl4mhealth/ssl_comparison

공식 코드

Self-Supervised Learning for Time Series: Contrastive or Generative?

https://github.com/eai-lab/on-device-sora

공식 코드

On-device Sora: Enabling Training-Free Diffusion-based Text-to-Video Generation for Mobile Devices

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