https://github.com/megvii-research/Arch-Net
공식 코드Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
algorithme utiliser
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
Cascade Prompt Learning for Vision-Language Model Adaptation
Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations
PerSRV: Personalized Sticker Retrieval with Vision-Language Model
LLM2CLIP: Powerful Language Model Unlocks Richer Visual Representation
Distance Learner: Incorporating Manifold Prior to Model Training
Graph Generative Model for Benchmarking Graph Neural Networks
Model-based Lifelong Reinforcement Learning with Bayesian Exploration
Utilizing Explainability Techniques for Reinforcement Learning Model Assurance
Shallow-UWnet : Compressed Model for Underwater Image Enhancement
PoseFix: Model-agnostic General Human Pose Refinement Network
HybridAugment++: Unified Frequency Spectra Perturbations for Model Robustness
Latent Diffusion Model for Conditional Reservoir Facies Generation
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts
Mixup Model Merge: Enhancing Model Merging Performance through Randomized Linear Interpolation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.