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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/forecastingresearch/forecastbench

공식 코드

ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities

https://github.com/forgee-master/HADL

공식 코드

HADL Framework for Noise Resilient Long-Term Time Series Forecasting

https://github.com/foroughp/manipulating-and-measuring-model-interpretability

공식 코드

Manipulating and Measuring Model Interpretability

https://github.com/fqjin/swei-net

공식 코드

SweiNet: Deep Learning Based Uncertainty Quantification for Ultrasound Shear Wave Elasticity Imaging

https://github.com/fracapuano/temporl

공식 코드

TempoRL: laser pulse temporal shape optimization with Deep Reinforcement Learning

https://github.com/frakkerman/ooh_code

공식 코드

Learning Dynamic Selection and Pricing of Out-of-Home Deliveries

https://github.com/francesco-sovrano/doxpy

공식 코드

An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability

https://github.com/franciszchen/surgbox

공식 코드

SurgBox: Agent-Driven Operating Room Sandbox with Surgery Copilot

https://github.com/frankzheng2022/prise

공식 코드

PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control

https://github.com/frederikpahde/rrclarc

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From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space

https://github.com/fredhohman/summit

공식 코드

Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations

https://github.com/fredhohman/summit-data

공식 코드

Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations

https://github.com/fredhohman/summit-notebooks

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Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations

https://github.com/freedomintelligence/chain-of-diagnosis

공식 코드

CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis

https://github.com/frenkowski/scimai-gym

공식 코드

Comparing Deep Reinforcement Learning Algorithms in Two-Echelon Supply Chains

https://github.com/frmicheli/WDRBO

공식 코드

Wasserstein Distributionally Robust Bayesian Optimization with Continuous Context

https://github.com/frt03/generalized_dt

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Generalized Decision Transformer for Offline Hindsight Information Matching

https://github.com/frt03/mxt_bench

공식 코드

A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation

https://github.com/fudan-zvg/reason2drive

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Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving

https://github.com/fudong03/mmst-vit

공식 코드

MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformer

https://github.com/fuqichen1998/SequentialVotingDet

공식 코드

Sequential Voting with Relational Box Fields for Active Object Detection

https://github.com/fuxiailab/civagent

공식 코드

Digital Player: Evaluating Large Language Models based Human-like Agent in Games

https://github.com/fuxiailab/xrl-bench

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XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques

https://github.com/fvialibre/edia

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A methodology to characterize bias and harmful stereotypes in natural language processing in Latin America

https://github.com/gabriele-dominici/causalcgm

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Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning

https://github.com/gabriele-dominici/counterfactual-cbm

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Counterfactual Concept Bottleneck Models

https://github.com/gaopiaoliang/Evidential

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Credible Remote Sensing Scene Classification Using Evidential Fusion on Aerial-Ground Dual-view Images

https://github.com/gaperez64/pomdps-reveal

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Revelations: A Decidable Class of POMDPs with Omega-Regular Objectives

https://github.com/garyzyr001/rethinking-airl

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Rethinking Adversarial Inverse Reinforcement Learning: Policy Imitation, Transferable Reward Recovery and Algebraic Equilibrium Proof

https://github.com/gautierdag/plancraft

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Plancraft: an evaluation dataset for planning with LLM agents

https://github.com/gchowell/bayesianfitforecast

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BayesianFitForecast: A User-Friendly R Toolbox for Parameter Estimation and Forecasting with Ordinary Differential Equations

https://github.com/gdam90/hyp2nav

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Hyp2Nav: Hyperbolic Planning and Curiosity for Crowd Navigation

https://github.com/ge25nab/Awesome-VLM-AD-ITS

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Vision Language Models in Autonomous Driving: A Survey and Outlook

https://github.com/geethen/geeconformal

공식 코드

Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction

https://github.com/gegewen/ufno

공식 코드

U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow

https://github.com/genglongling/SagaLLM

공식 코드

SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning

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