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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MVerghese/NN-Dynamics-Sparse-Reward
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
https://github.com/Machine-Learning-for-Everyone-ML4E/CoP-Code-of-Papers
https://github.com/MachineLearningJournalClub/LearningNLP
https://github.com/MartinPawel/ProbabilisticallyRobustRecourse
Learning Model-Agnostic Counterfactual Explanations for Tabular Data
https://github.com/Mayurji/Image-Classification-PyTorch
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/Mind23-2/MindCode-101/tree/main/OctSqueeze
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression
https://github.com/Mind23-2/MindCode-140
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
https://github.com/Mind23-2/MindCode-37
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindCode-4/code-1/tree/main/vision_text_dual_encoder
Distilled Dual-Encoder Model for Vision-Language Understanding
https://github.com/MindCode-4/code-11/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MindCode-4/code-12/tree/main/gated-word-character-recurrent-language-model
https://github.com/MindCode-4/code-13/tree/main/RAF-ms-main
https://github.com/MindCode-4/code-3/tree/main/florence2
https://github.com/MindCode-4/code-5/tree/main/vision_text_dual_encoder
Distilled Dual-Encoder Model for Vision-Language Understanding
https://github.com/MindCode-4/code-5/tree/main/wavlm
https://github.com/MindCode-4/code-6/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MindCode-4/code-7/tree/main/gated-word-character-recurrent-language-model
https://github.com/MindCode-4/code-8/tree/main/Neural-Network-based-Speech-Enhancement
Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning
https://github.com/MindCode-4/code-8/tree/main/RAF-ms-main
https://github.com/MindSpore-paper-code-2/code2/tree/main/OctSqueeze
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression
https://github.com/MindSpore-paper-code-2/code399/tree/main/ctcmodel
CTCModel: a Keras Model for Connectionist Temporal Classification
https://github.com/MindSpore-paper-code-2/code400/tree/main/Efficientnet
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-paper-code-3/code2/tree/main/darknet53
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-paper-code-3/code8/tree/main/darknet53
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-paper-code-3/code8/tree/main/efficientnet-b0
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/MindSpore-scientific-2/code-12/tree/main/gated-word-character-recurrent-language-model
https://github.com/MindSpore-scientific-2/code-14/tree/main/jamba
https://github.com/MindSpore-scientific-2/code-4/tree/main/Block_Model
https://github.com/MindSpore-scientific-2/code-5/tree/main/Block_Model
https://github.com/MindSpore-scientific/code-11/tree/main/Patient2Vec-A-Personalized-Interpretable
https://github.com/MindSpore-scientific/code-13/tree/main/Patient2Vec-A-Personalized-Interpretable
https://github.com/MindSpore-scientific/code-3/tree/main/a-self-attentive-model-for-knowledge-tracing
https://github.com/MiuGod0126/ConvS2S_Paddle
https://github.com/ModelOriented/DrWhy
https://github.com/ModelOriented/EloML
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.