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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/baselm/cmarl

공식 코드

A Deep Recurrent Q Network towards Self-adapting Distributed Microservices architecture

https://github.com/bashivanlab/iwisdm

공식 코드

IWISDM: Assessing instruction following in multimodal models at scale

https://github.com/bayesflow-org/SA-ABI

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Sensitivity-Aware Amortized Bayesian Inference

https://github.com/bayesflow-org/hierarchical-model-comparison

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A Deep Learning Method for Comparing Bayesian Hierarchical Models

https://github.com/bayesflow-org/non-stationary-ddm-validation

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Validation and Comparison of Non-Stationary Cognitive Models: A Diffusion Model Application

https://github.com/bayesomicslab/OUD-Risk-Prediction

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Improving Opioid Use Disorder Risk Modelling through Behavioral and Genetic Feature Integration

https://github.com/bear96/gabm-epidemic

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Epidemic Modeling with Generative Agents

https://github.com/behavioral-data/blade

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BLADE: Benchmarking Language Model Agents for Data-Driven Science

https://github.com/behaviorguidedRL/BGRL

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Learning to Score Behaviors for Guided Policy Optimization

https://github.com/belindal/LaMPP

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LaMPP: Language Models as Probabilistic Priors for Perception and Action

https://github.com/bemporad/gnep-learn

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An active learning method for solving competitive multi-agent decision-making and control problems

https://github.com/benchoi93/TrajGAIL

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TrajGAIL: Generating Urban Vehicle Trajectories using Generative Adversarial Imitation Learning

https://github.com/berkeleyautomation/iifl

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IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors

https://github.com/berkeleyexpertsystemtechnologieslab/evsivslstm

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Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information

https://github.com/bethgelab/notorious_difficulty_of_comparing_human_and_machine_perception

공식 코드

Five Points to Check when Comparing Visual Perception in Humans and Machines

https://github.com/bezirganyan/DBF_uncertainty

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Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion

https://github.com/bezirganyan/luma

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LUMA: A Benchmark Dataset for Learning from Uncertain and Multimodal Data

https://github.com/bharathichezhiyan/TamilMixSentiment

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Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Text

https://github.com/bhouri0412/rpn_bo

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Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks

https://github.com/bigai-ai/adasociety

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AdaSociety: An Adaptive Environment with Social Structures for Multi-Agent Decision-Making

https://github.com/bigai-ai/civrealm

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CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents

https://github.com/binging512/icfnet

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ICFNet: Integrated Cross-modal Fusion Network for Survival Prediction

https://github.com/bio-hpc/sibila

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SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts

https://github.com/bioinformatics-ua/patienttm

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Modelling Patient Trajectories Using Multimodal Information

https://github.com/biomedia-mira/chexploration

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Algorithmic encoding of protected characteristics in image-based models for disease detection

https://github.com/biomedia-mira/cxr-foundation-bias

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Risk of Bias in Chest Radiography Deep Learning Foundation Models

https://github.com/biswajitsadhu/raddqn

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RadDQN: a Deep Q Learning-based Architecture for Finding Time-efficient Minimum Radiation Exposure Pathway

https://github.com/biswassanket/docsegtr

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DocSegTr: An Instance-Level End-to-End Document Image Segmentation Transformer

https://github.com/bit1029public/ADRQN

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On Improving Deep Reinforcement Learning for POMDPs

https://github.com/blender-nlp/smartbook

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SmartBook: AI-Assisted Situation Report Generation for Intelligence Analysts

https://github.com/blurryface0814/pcpnet

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PCPNet: An Efficient and Semantic-Enhanced Transformer Network for Point Cloud Prediction

https://github.com/blyucs/autogmap

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AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars

https://github.com/bobby-he/uncertainr

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UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography

https://github.com/bobwu1998/uncertainty_quant_all

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Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies

https://github.com/bolt-research/popgym_arcade

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POPGym Arcade: Parallel Pixelated POMDPs

https://github.com/boreshkinai/nbeats-midterm

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N-BEATS neural network for mid-term electricity load forecasting

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