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/dmrimawi/cais-dma
공식 코드CAIS-DMA: A Decision-Making Assistant for Collaborative AI Systems
https://github.com/dmu-xmu/dsr
공식 코드https://github.com/dniku/free-lunch-saliency
공식 코드https://github.com/dnishio/DSAC
공식 코드https://github.com/docu-lab/differentiable_dro_layers
공식 코드https://github.com/doerlbh/ABaCoDE
공식 코드https://github.com/doerlbh/BanditZoo
공식 코드Evolutionary Multi-Armed Bandits with Genetic Thompson Sampling
https://github.com/doerlbh/BerlinUCB
공식 코드Online Semi-Supervised Learning in Contextual Bandits with Episodic Reward
https://github.com/doerlbh/HumanLSTM
공식 코드Predicting human decision making in psychological tasks with recurrent neural networks
https://github.com/doerlbh/mentalRL
공식 코드A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry
https://github.com/dominickrei/poseawarevt
공식 코드Seeing the Pose in the Pixels: Learning Pose-Aware Representations in Vision Transformers
https://github.com/donamin/self-imitation-learning
공식 코드Self-Imitation Learning of Locomotion Movements through Termination Curriculum
https://github.com/dongyh20/octopus
공식 코드Octopus: Embodied Vision-Language Programmer from Environmental Feedback
https://github.com/dorisscma/fairgridsearch
공식 코드FairGridSearch: A Framework to Compare Fairness-Enhancing Models
https://github.com/dornik/reagent
공식 코드ReAgent: Point Cloud Registration using Imitation and Reinforcement Learning
https://github.com/dqwang122/salam
공식 코드Learning from Mistakes via Cooperative Study Assistant for Large Language Models
https://github.com/dracosource/draco
공식 코드Multi-Agent Distributed Reinforcement Learning for Making Decentralized Offloading Decisions
https://github.com/dravyanshsharma/adversarial-contrastive
공식 코드https://github.com/drewtnguyen/risk-tradeoffs-experiments
공식 코드Data-Adaptive Tradeoffs among Multiple Risks in Distribution-Free Prediction
https://github.com/drl-casia/autonomous-driving
공식 코드Lane Change Decision-Making through Deep Reinforcement Learning
https://github.com/ds4dm/branch-search-trees
공식 코드Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies
https://github.com/ds4dm/ecole-paper
공식 코드https://github.com/ds4dm/learn2branch
공식 코드Exact Combinatorial Optimization with Graph Convolutional Neural Networks
https://github.com/dsbrown1331/CoRL2019-DREX
공식 코드Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations
https://github.com/dsbrown1331/bayesianrex
공식 코드Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
https://github.com/dsbrown1331/broil
공식 코드https://github.com/dsbrown1331/machine-teaching-irl
공식 코드Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications
https://github.com/dschinagl/occam
공식 코드OccAM's Laser: Occlusion-based Attribution Maps for 3D Object Detectors on LiDAR Data
https://github.com/dsg-polymtl/flockmtl
공식 코드Beyond Quacking: Deep Integration of Language Models and RAG into DuckDB
https://github.com/dsitnik/lefm
공식 코드https://github.com/dssg/aequitas
공식 코드https://github.com/dstl/yawning-titan
공식 코드Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulation
https://github.com/dtak/POPCORN-POMDP
공식 코드POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning
https://github.com/dtak/power-constrained-bandits-public
공식 코드https://github.com/dtroop/evt-bandits
공식 코드Risk-Averse Action Selection Using Extreme Value Theory Estimates of the CVaR
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.