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Decision Making

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Taeseong-Han/ECGNoiseQuantification

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Diffusion-Based Electrocardiography Noise Quantification via Anomaly Detection

https://github.com/TaikiMiyagawa/SPRT-TANDEM

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Sequential Density Ratio Estimation for Simultaneous Optimization of Speed and Accuracy

https://github.com/TeaPearce/Counter-Strike_Behavioural_Cloning

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Counter-Strike Deathmatch with Large-Scale Behavioural Cloning

https://github.com/Teddyzander/FairR

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How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies

https://github.com/Tencent/TStarBots

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TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game

https://github.com/TheEngineRoom-UniGe/ANDOR

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A Hierarchical Architecture for Human-Robot Cooperation Processes

https://github.com/TheOpenSI/CoSMIC

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Unleashing Artificial Cognition: Integrating Multiple AI Systems

https://github.com/Thinklab-SJTU/awesome-ml4co

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Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching

https://github.com/TianhongDai/esil-hindsight

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Episodic Self-Imitation Learning with Hindsight

https://github.com/TillmannRheude/SegHiResGrad_CAM

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Leveraging CAM Algorithms for Explaining Medical Semantic Segmentation

https://github.com/TimCJanke/PMAPS2020_IGEP

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Probabilistic multivariate electricity price forecasting using implicit generative ensemble post-processing

https://github.com/Tinker-Twins/Robust_Behavioral_Cloning

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Robust Behavioral Cloning for Autonomous Vehicles using End-to-End Imitation Learning

https://github.com/TongZhangTHU/sgr

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Leveraging Locality to Boost Sample Efficiency in Robotic Manipulation

https://github.com/TonyXuQAQ/Topo-boundary

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iCurb: Imitation Learning-based Detection of Road Curbs using Aerial Images for Autonomous Driving

https://github.com/TorchCraft/StarData

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STARDATA: A StarCraft AI Research Dataset

https://github.com/UCLA-StarAI/LearnFairNB

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Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns

https://github.com/UKPLab/emnlp2020-faithful-rationales

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Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision

https://github.com/UKPLab/ijcai2019-relis

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Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation

https://github.com/USC-InfoLab/busyness-graph-neural-network

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Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting

https://github.com/USTCAVSA/TSL

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Traffic Scenario Logic: A Spatial-Temporal Logic for Modeling and Reasoning of Urban Traffic Scenarios

https://github.com/UVa-NLP/HEDGE

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Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection

https://github.com/Ukeyboard/dcap

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Revisiting Local Descriptor for Improved Few-Shot Classification

https://github.com/Unbabel/COMET

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The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics

https://github.com/V-i-g-n-e-s-h-N/VERITAS

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VERITAS: Verification and Explanation of Realness in Images for Transparency in AI Systems

https://github.com/VIRL-Platform/VIRL

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V-IRL: Grounding Virtual Intelligence in Real Life

https://github.com/VITA-Group/L2O-Training-Techniques

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Training Stronger Baselines for Learning to Optimize

https://github.com/VITA-Group/VGAI

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Scalable Perception-Action-Communication Loops with Convolutional and Graph Neural Networks

https://github.com/Valdecy/pyDecision

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Enhancing Decision Analysis with a Large Language Model: pyDecision a Comprehensive Library of MCDA Methods in Python

https://github.com/VinAIResearch/PC3-pytorch

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Predictive Coding for Locally-Linear Control

https://github.com/VishnuDuttSharma/deep-multirobot-task

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Graph Neural Networks for Decentralized Multi-Robot Submodular Action Selection

https://github.com/VittorioGiammarino/Learning-from-humans-combining-imitation-and-deep-on-policy-reinforcement-learning-to-accomplish-su

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Combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task

https://github.com/VittorioGiammarino/Online_BWforHIL

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Online Baum-Welch algorithm for Hierarchical Imitation Learning

https://github.com/WangHanLinHenry/STeCa

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STeCa: Step-level Trajectory Calibration for LLM Agent Learning

https://github.com/WangLibo1995/GeoSeg

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Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images

https://github.com/Wei9711/GACG

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Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning

https://github.com/WindyLee0822/Process_Q_Model

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Process Reward Model with Q-Value Rankings

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.