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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/aair-lab/grapl

공식 코드

Epistemic Exploration for Generalizable Planning and Learning in Non-Stationary Settings

https://github.com/aair-lab/qace

공식 코드

Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings (Extended Version)

https://github.com/aaltoml/calibrated-dnn

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Fixing Overconfidence in Dynamic Neural Networks

https://github.com/aaltopml/zero-shot-assistance-in-novel-decision-problems

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Zero-Shot Assistance in Sequential Decision Problems

https://github.com/aamitssharma07/SAL-Cryptopulse

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CryptoPulse: Short-Term Cryptocurrency Forecasting with Dual-Prediction and Cross-Correlated Market Indicators

https://github.com/aangelopoulos/private_prediction_sets

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Private Prediction Sets

https://github.com/aangelopoulos/rcps

공식 코드

Distribution-Free, Risk-Controlling Prediction Sets

https://github.com/aaron-wheeler/brokerage.jl

공식 코드

Scalable Agent-Based Modeling for Complex Financial Market Simulations

https://github.com/aaron-wheeler/tradingagents.jl

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Scalable Agent-Based Modeling for Complex Financial Market Simulations

https://github.com/aaronwalsman/ltron-torch

공식 코드

Learning to Build by Building Your Own Instructions

https://github.com/aashrivastava/llmwargaminginconsistency

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Measuring Free-Form Decision-Making Inconsistency of Language Models in Military Crisis Simulations

https://github.com/aatifjiwani/rgb-footprint-extract

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A Semantic Segmentation Network for Urban-Scale Building Footprint Extraction Using RGB Satellite Imagery

https://github.com/abhi23run/cse8803_dlt_project

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Numerical Reasoning for Financial Reports

https://github.com/abhi460729/Action-Duration-with-Contextual-Bandits-for-Deep-Reinforcement-Learning-in-Dynamic-Environments

공식 코드

Adaptive Action Duration with Contextual Bandits for Deep Reinforcement Learning in Dynamic Environments

https://github.com/abhi4ssj/QuickNATv2

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QuickNAT: A Fully Convolutional Network for Quick and Accurate Segmentation of Neuroanatomy

https://github.com/abhiksingla/UAV_obstacle_avoidance_controller

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Memory-based Deep Reinforcement Learning for Obstacle Avoidance in UAV with Limited Environment Knowledge

https://github.com/abirhossen786/ums

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Total Nitrogen Estimation in Agricultural Soils via Aerial Multispectral Imaging and LIBS

https://github.com/abonte/protopdebug

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Concept-level Debugging of Part-Prototype Networks

https://github.com/ac-rad/organa

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ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization

https://github.com/acatai/pn-mcts

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Proof Number Based Monte-Carlo Tree Search

https://github.com/acellera/acegen-open

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ACEGEN: Reinforcement learning of generative chemical agents for drug discovery

https://github.com/acostarelli/meta-models-public

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Meta-Models: An Architecture for Decoding LLM Behaviors Through Interpreted Embeddings and Natural Language

https://github.com/acotai/kunpeng

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KUNPENG: An Embodied Large Model for Intelligent Maritime

https://github.com/activeloopai/deeplake

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Deep Lake: a Lakehouse for Deep Learning

https://github.com/adagorgun/vital

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VITAL: More Understandable Feature Visualization through Distribution Alignment and Relevant Information Flow

https://github.com/adaruna3/explainable-kge

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Explainable Knowledge Graph Embedding: Inference Reconciliation for Knowledge Inferences Supporting Robot Actions

https://github.com/adelaidehsu/path_model_evaluation

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Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making

https://github.com/adibka/RIZE

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RIZE: Regularized Imitation Learning via Distributional Reinforcement Learning

https://github.com/adishs/neurips2021_curriculum-teaching-demonstrations_code

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Curriculum Design for Teaching via Demonstrations: Theory and Applications

https://github.com/aditya-taparia/batcave

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Trustworthy Conceptual Explanations for Neural Networks in Robot Decision-Making

https://github.com/adityalab/camul

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CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting

https://github.com/admantwerp/llm-tradeoffs

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Cash or Comfort? How LLMs Value Your Inconvenience

https://github.com/adrianhutter/learning_with_opponent_transparency

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Learning in two-player games between transparent opponents

https://github.com/adriano-lucieri/shape-bias-in-dermoscopy

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Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification

https://github.com/agentification/language-integrated-vi

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How Can LLM Guide RL? A Value-Based Approach

https://github.com/agi-brain/cee

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Reducing Action Space for Deep Reinforcement Learning via Causal Effect Estimation

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