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Attension-Transformer-预训练/BERT Pre-training of Deep Bidirectional Transformers forLanguage Understanding.pdf Normal file

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Attension-Transformer-预训练/Dosovitskiy et al., 2020. An Image is Worth 16x16 Words Transformers for Image Recognition at Scale.pdf Normal file

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Attension-Transformer-预训练/NeurIPS-2020-language-models-are-few-shot-learners-Paper.pdf Normal file

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Attension-Transformer-预训练/Neural Machine Translation by Jointly Learning to Align and Translate .pdf Normal file

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Attension-Transformer-预训练/Vaswani et al., 2017. Attention is All You Need.pdf Normal file

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CNN/Deep Residual Learning for Image Recognition(4).pdf Normal file

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CNN/Very Deep Convolutional Networks for Large-Scale ImageRecognition(4).pdf Normal file

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NLP发展/Hochreiter & Schmidhuber, Long Short-Term Memory.pdf Normal file

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NLP发展/Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation.pdf Normal file

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RNN/循环神经网络研究综述_杨丽.pdf Normal file

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Reinforced-Learning/Enhanced DQN Framework for Selecting Actions and Updating.pdf Normal file

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Reinforced-Learning/Enhanced Reinforcement Learning Method Combining.pdf Normal file

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Reinforced-Learning/Mnih et al., 2015. Human-level control through deep reinforcement learning （DQN）.pdf Normal file

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Reinforced-Learning/Silver et al., 2016. Mastering the game of Go with deep neural networks and tree search.pdf Normal file

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RL-Mahjong/A hierarchical branch and bound algorithm for Mahjong deficiency.pdf → 游戏AI/RL-Mahjong/A hierarchical branch and bound algorithm for Mahjong deficiency.pdf

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RL-Mahjong/A novel deep residual network-based incompleteinformation competition strategy for four-playersMahjong gamesMingyan Wang1 · Tianwei Yan1 · Mingyuan Luo1 · Wei Huang12019.pdf → 游戏AI/RL-Mahjong/A novel deep residual network-based incompleteinformation competition strategy for four-playersMahjong gamesMingyan Wang1 · Tianwei Yan1 · Mingyuan Luo1 · Wei Huang12019.pdf

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RL-Mahjong/An analysis of play style of advanced mahjongplayers toward the implementation of strong AIplayerHiroshi Sato, Tomohiro Shirakawa, Akitoshi Hagihara & Kento Maeda2017.pdf → 游戏AI/RL-Mahjong/An analysis of play style of advanced mahjongplayers toward the implementation of strong AIplayerHiroshi Sato, Tomohiro Shirakawa, Akitoshi Hagihara & Kento Maeda2017.pdf

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RL-Mahjong/An efficient AI-based method to play the Mahjong game with theknowledge and game-tree searching strategyMingyan Wang2021.pdf → 游戏AI/RL-Mahjong/An efficient AI-based method to play the Mahjong game with theknowledge and game-tree searching strategyMingyan Wang2021.pdf

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RL-Mahjong/Applying Importance Sampling to MCTS for MahjongIEEE Transactions on Games, 2025.pdf → 游戏AI/RL-Mahjong/Applying Importance Sampling to MCTS for MahjongIEEE Transactions on Games, 2025.pdf

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RL-Mahjong/Applying_Importance_Sampling_to_MCTS_for_Mahjong.pdf → 游戏AI/RL-Mahjong/Applying_Importance_Sampling_to_MCTS_for_Mahjong.pdf

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RL-Mahjong/Building_a_computer_Mahjong_player_based_on_Monte_Carlo_simulation_and_opponent_models.pdf → 游戏AI/RL-Mahjong/Building_a_computer_Mahjong_player_based_on_Monte_Carlo_simulation_and_opponent_models.pdf

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RL-Mahjong/Card Protocols that Allow You to Switch Cardsto Mahjong TilesYuji Suga1,a)Received July 10, 2024, Accepted January 10, 2025.pdf → 游戏AI/RL-Mahjong/Card Protocols that Allow You to Switch Cardsto Mahjong TilesYuji Suga1,a)Received July 10, 2024, Accepted January 10, 2025.pdf

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RL-Mahjong/International Journal of Intelligent Systems - 2024 - Li - LsAc ‐MJ A Low‐Resource Consumption Reinforcement Learning.pdf → 游戏AI/RL-Mahjong/International Journal of Intelligent Systems - 2024 - Li - LsAc ‐MJ A Low‐Resource Consumption Reinforcement Learning.pdf

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RL-Mahjong/Method for Constructing Artificial IntelligencePlayer with Abstractions to Markov DecisionProcesses in Multiplayer Game of MahjongMoyuru Kurita∗and Kunihito Hoki†∗Heroz Inc., †The University of Electro-Communications2021.pdf → 游戏AI/RL-Mahjong/Method for Constructing Artificial IntelligencePlayer with Abstractions to Markov DecisionProcesses in Multiplayer Game of MahjongMoyuru Kurita∗and Kunihito Hoki†∗Heroz Inc., †The University of Electro-Communications2021.pdf

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RL-Mahjong/Official International Mahjong A New Playground for AI Research2023.pdf → 游戏AI/RL-Mahjong/Official International Mahjong A New Playground for AI Research2023.pdf

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RL-Mahjong/Research_on_the_Imperfect_Information_Game_of_Four-Player_Mahjong_Based_on_Mix-PPO.pdf → 游戏AI/RL-Mahjong/Research_on_the_Imperfect_Information_Game_of_Four-Player_Mahjong_Based_on_Mix-PPO.pdf

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RL-Mahjong/The enduring appeal of Mahjong Navigating the challenges of AI integration.pdf → 游戏AI/RL-Mahjong/The enduring appeal of Mahjong Navigating the challenges of AI integration.pdf

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RL-Mahjong/theory-and-applications-of-satisfiability-testing--sat-2021-2021.pdf → 游戏AI/RL-Mahjong/theory-and-applications-of-satisfiability-testing--sat-2021-2021.pdf

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RL-Mahjong/“拱猪”游戏的深度蒙特卡洛博弈算法_吴立成.pdf → 游戏AI/RL-Mahjong/“拱猪”游戏的深度蒙特卡洛博弈算法_吴立成.pdf

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RL-Mahjong/大众麻将的博弈系统研究2021.pdf → 游戏AI/RL-Mahjong/大众麻将的博弈系统研究2021.pdf

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游戏AI/RL-Mahjong/深度强化学习进展从AlphaGo到AlphaGo Zero_唐振韬.pdf Normal file

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游戏AI/五子棋/基于MCTS和卷积神经网络的五子棋策略研究_欧俊臣.pdf Normal file

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游戏AI/五子棋/基于α-β剪枝算法的五子棋游戏设计与实现.pdf Normal file

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游戏AI/五子棋/基于计算机博弈的五子棋AI设计_郑培铭.pdf Normal file

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生成式AI/Goodfellow et al., 2014. Generative Adversarial Nets .pdf Normal file

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生成式AI/Ho et al., 2020. Denoising Diffusion Probabilistic Models.pdf Normal file

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生成式AI/NeurIPS-2020-denoising-diffusion-probabilistic-models-Paper.pdf Normal file

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生成式AI/Radford et al., 2015. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.pdf Normal file

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神经网络基础/ImageNet Classification with Deep Convolutional Neural Networks.pdf Normal file

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神经网络基础/LeCun et al., 1998. Gradient-based learning applied to document recognition.pdf Normal file

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神经网络基础/Learning representations by back-propagating errors.pdf Normal file

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神经网络基础/The perceptron A probabilistic model for information storage and organization in the brain 感知器 rosenblatt1958.pdf Normal file

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