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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/machine-teaching-group/ijcai2024-task-embeddings-rl

공식 코드

Learning Embeddings for Sequential Tasks Using Population of Agents

https://github.com/machine-teaching-group/task-embeddings-rl

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Learning Embeddings for Sequential Tasks Using Population of Agents

https://github.com/machine-teaching-group/tmlr2024_neurtasksyn

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Neural Task Synthesis for Visual Programming

https://github.com/mackelab/amortized-decision-making

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Amortized Bayesian Decision Making for simulation-based models

https://github.com/mackelab/labproject

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A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science

https://github.com/mad-stat/parnn

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Probabilistic AutoRegressive Neural Networks for Accurate Long-range Forecasting

https://github.com/madisoncoots/equitable-algorithms

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Designing Equitable Algorithms

https://github.com/magicgh/ask-before-plan

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Ask-before-Plan: Proactive Language Agents for Real-World Planning

https://github.com/maikejulie/DNN4Cli/tree/main/THOR/BayesianApproach

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Explainable Artificial Intelligence for Bayesian Neural Networks: Towards trustworthy predictions of ocean dynamics

https://github.com/mail-ecnu/text-gym-agents

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Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym

https://github.com/majeed7/mcdmfallacies_compositional

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Unveiling and unraveling aggregation and dispersion fallacies in group MCDM

https://github.com/mal84emma/Building-Design-VoI

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Quantifying the benefit of load uncertainty reduction for the design of district energy systems under grid constraints using the Value of Information

https://github.com/mamadpierre/DNN-SMEIO

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Simultaneous Decision Making for Stochastic Multi-echelon Inventory Optimization with Deep Neural Networks as Decision Makers

https://github.com/mandycoston/counterfactual

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Counterfactual Risk Assessments, Evaluation, and Fairness

https://github.com/manikanta-72/sensitivity-of-llm-s-decision-making-capabilities

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Exploring the Sensitivity of LLMs' Decision-Making Capabilities: Insights from Prompt Variation and Hyperparameters

https://github.com/manjaryp/ganvsgraphicsvsreal

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Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNet

https://github.com/manome/python-mab

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Simple Modification of the Upper Confidence Bound Algorithm by Generalized Weighted Averages

https://github.com/manuel-rdz/c-tran

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Multi-Label Retinal Disease Classification using Transformers

https://github.com/manueleberhardinger/ec-rl

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Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments

https://github.com/manueleberhardinger/unveiling-rl-with-gp

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Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming

https://github.com/manutdmoon/bikc

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BiKC: Keypose-Conditioned Consistency Policy for Bimanual Robotic Manipulation

https://github.com/maohangyu/TIT_open_source

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Transformer in Transformer as Backbone for Deep Reinforcement Learning

https://github.com/maohangyu/pdit

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PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning

https://github.com/maoliyuan/odice-pytorch

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ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update

https://github.com/marc-rigter/1r2r

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One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning

https://github.com/marcelbinz/centaur

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Turning large language models into cognitive models

https://github.com/marcometer/endless-memory-gym

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Memory Gym: Towards Endless Tasks to Benchmark Memory Capabilities of Agents

https://github.com/marcomussi/dlb

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Dynamical Linear Bandits

https://github.com/markin-wang/camanet

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CAMANet: Class Activation Map Guided Attention Network for Radiology Report Generation

https://github.com/marko-ruman/RL-Correspondence-Learner

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Knowledge Transfer in Deep Reinforcement Learning via an RL-Specific GAN-Based Correspondence Function

https://github.com/marko-vasic/moet

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MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning

https://github.com/marko-zaric/action-prototype-gen

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Unsupervised Learning of Effective Actions in Robotics

https://github.com/marmotlab/fcmnet

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FCMNet: Full Communication Memory Net for Team-Level Cooperation in Multi-Agent Systems

https://github.com/marpogaus/stplf-bnf

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Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows

https://github.com/marrlab/milple

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Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images

https://github.com/marsgokturk/gpt3-false-political-statement-detection

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Assessing the Effectiveness of GPT-3 in Detecting False Political Statements: A Case Study on the LIAR Dataset

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