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Rubik's Cube
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Solving the Rubik's Cube is a pathfinding task on a massive implicit graph.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/WolfgangKonen/PapersWithCodeOthello
공식 코드AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time
https://github.com/adaptivesubgoalsearch/adaptive_subs
공식 코드Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
https://github.com/brucewang123456789/GeniusTrail
공식 코드Wormhole Memory: A Rubik's Cube for Cross-Dialogue Retrieval
https://github.com/deepmind/levintreesearch_cm
공식 코드https://github.com/google-deepmind/levintreesearch_cm
공식 코드https://github.com/gshartnett/rubiks-clifford-synthesis
공식 코드https://github.com/huawei-noah/CV-backbones
공식 코드Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/huawei-noah/ghostnet/tree/master/tinynet_pytorch
공식 코드Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/k1242/cayleypy-cube
공식 코드https://github.com/kyo-takano/EfficientCube
공식 코드https://github.com/mfinzi/equivariant-MLP
공식 코드A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
https://github.com/subgoal-search/subgoal-search
공식 코드https://github.com/yu-fangxu/for
공식 코드Flow of Reasoning:Training LLMs for Divergent Problem Solving with Minimal Examples
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tinynet
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/AIDude-eng/projection-path-explorer-page
ProjectionPathExplorer: Exploring Visual Patterns in Projected Decision-Making Paths
https://github.com/AashrayAnand/rubiks-cube-reinforcement-learning
https://github.com/Dalkio/RL_rubiks
https://github.com/JasperBusschers/multi-objective-Rubik-s-cube
https://github.com/KeatonMueller/rl-cube
https://github.com/MindSpore-paper-code-2/code3/tree/main/tinynet
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/bay3s/auto-dr
https://github.com/eyeeco/Rubick-s-Cube-Dataset
https://github.com/james77777778/keras-image-models
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/jiajunhua/CV-Backbones
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/kaletap/deep-cube-rl
https://github.com/leondgarse/keras_cv_attention_models/tree/main/keras_cv_attention_models/mobilenetv3_family
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/mindspore-ai/models/tree/master/research/cv/tinynet
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/mkovalski/cs4995_cube
https://github.com/nascarsayan/dl-rubiks-autodidactic-solver
https://github.com/nathangrinsztajn/rubiks_cube
https://github.com/researchworking/scalaremlp
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
https://github.com/robbiejones96/RubiksSolver
https://github.com/rwightman/pytorch-image-models
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
https://github.com/sabeaussan/ROS_Unity
https://github.com/weichiyao/scalaremlp
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.