Papers with Code 아카이브
Decision Making
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/guoyihonggyh/Off-Dynamics-Reinforcement-Learning-via-Domain-Adaptation-and-Reward-Augmented-Imitation
공식 코드Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
https://github.com/gurkirt/3D-RetinaNet
공식 코드ROAD: The ROad event Awareness Dataset for Autonomous Driving
https://github.com/gurkirt/road-dataset
공식 코드ROAD: The ROad event Awareness Dataset for Autonomous Driving
https://github.com/guruprasad93/flexiblemachinelearning
공식 코드Engineering flexible machine learning systems by traversing functionally-invariant paths
https://github.com/gustavokcouto/hgail
공식 코드https://github.com/gwr3n/jsdp
공식 코드https://github.com/h-aboutalebi/covidbiochem
공식 코드https://github.com/haarnoja/sac
공식 코드Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
https://github.com/hadijahanshahi/adptriage
공식 코드https://github.com/hadoov/scorpius3d
공식 코드A simple method for decision making in robocup soccer simulation 3d environment
https://github.com/hahmdy/causal_influence_prompting
공식 코드https://github.com/hai-chao-zhang/oostraj
공식 코드OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising
https://github.com/halaa901/qnlp-thesis
공식 코드https://github.com/halid1020/agent-arena-v0
공식 코드Agent-Arena: A General Framework for Evaluating Control Algorithms
https://github.com/hamedhematian/importantnews
공식 코드KhabarChin: Automatic Detection of Important News in the Persian Language
https://github.com/hamidkarimi/DeepDIG
공식 코드Characterizing the Decision Boundary of Deep Neural Networks
https://github.com/hammerlabml/modelagnosticgroupfairnesscounterfactuals
공식 코드"Explain it in the Same Way!" -- Model-Agnostic Group Fairness of Counterfactual Explanations
https://github.com/hanglai/bmpo
공식 코드https://github.com/hangligit/btn
공식 코드The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding
https://github.com/hannahrosafriesacher/CalibrationStudy
공식 코드https://github.com/hanqingwangai/vxn
공식 코드https://github.com/hansenhua/ilid-offline-imitation-learning
공식 코드How to Leverage Diverse Demonstrations in Offline Imitation Learning
https://github.com/hansenhua/ollie-offline-to-online-imitation-learning
공식 코드OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning
https://github.com/hanyangzhong/situational_planning_datasets
공식 코드LLM-SAP: Large Language Models Situational Awareness Based Planning
https://github.com/hanyas/psoc
공식 코드Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing
https://github.com/haochihlin/ICRA2021
공식 코드No Need for Interactions: Robust Model-Based Imitation Learning using Neural ODE
https://github.com/haofanwang/Score-CAM
공식 코드Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks
https://github.com/haosulab/ManiSkill
공식 코드ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
https://github.com/haosulab/maniskill2
공식 코드ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
https://github.com/haotiansun14/adaplanner
공식 코드AdaPlanner: Adaptive Planning from Feedback with Language Models
https://github.com/haoyuan-l/fed_datamesh
공식 코드https://github.com/haozhu10015/hiql
공식 코드Multi-intention Inverse Q-learning for Interpretable Behavior Representation
https://github.com/happy-yan/DACER-Diffusion-with-Online-RL
공식 코드https://github.com/harfang3d/dogfight-sandbox-hg2
공식 코드https://github.com/hari-sikchi/DVL
공식 코드Dual RL: Unification and New Methods for Reinforcement and Imitation Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.