Papers with Code 아카이브

Decision Making Under Uncertainty

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/rothkopflab/nioc-neurips

공식 코드

Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs

https://github.com/saitcakmak/BoRisk

공식 코드

Bayesian Optimization of Risk Measures

https://github.com/samuelstanton/conformal-bayesopt

공식 코드

Bayesian Optimization with Conformal Prediction Sets

https://github.com/scope-lab-vu/PAMCTS

공식 코드

Decision Making in Non-Stationary Environments with Policy-Augmented Search

https://github.com/seanrsinclair/hindsight-learning

공식 코드

Hindsight Learning for MDPs with Exogenous Inputs

https://github.com/sisl/DreamrHHP

공식 코드

Dynamic Real-time Multimodal Routing with Hierarchical Hybrid Planning

https://github.com/sisl/SCoBA.jl

공식 코드

Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints

https://github.com/sjgershm/exploration

공식 코드

Comparing Exploration-Exploitation Strategies of LLMs and Humans: Insights from Standard Multi-armed Bandit Tasks

https://github.com/thxsxth/POMDP_RLSepsis

공식 코드

Unifying Cardiovascular Modelling with Deep Reinforcement Learning for Uncertainty Aware Control of Sepsis Treatment

https://github.com/tomyot/measurement-simplification

공식 코드

Measurement Simplification in ρ-POMDP with Performance Guarantees

https://github.com/vaishwarya96/maple-uncertainty-estimation

공식 코드

Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers

https://github.com/yairomer/ppde

공식 코드

Uncertainty Visualization via Low-Dimensional Posterior Projections

https://gitlab.com/vanparys/dusa

공식 코드

Optimal Learning for Structured Bandits

https://github.com/COHRINT/FaMSeC

Factorized Machine Self-Confidence for Decision-Making Agents

https://github.com/ENSTA-U2IS-AI/torch-uncertainty

Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification

https://github.com/GiaLacTRAN/convolutional_deep_gp_random_features

Calibrating Deep Convolutional Gaussian Processes

https://github.com/amzn/emukit

Emulation of physical processes with Emukit

https://github.com/dais-ita/SLProbLog

Probabilistic Logic Programming with Beta-Distributed Random Variables

https://github.com/giannifranchi/LP_BNN

Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification

https://github.com/khalil-research/neur2bilo

Neur2SP: Neural Two-Stage Stochastic Programming

https://github.com/khalil-research/neur2ro

Neur2SP: Neural Two-Stage Stochastic Programming

https://github.com/lily-x/combinatorial-rmab

Neur2SP: Neural Two-Stage Stochastic Programming

https://github.com/mrateike/fair_minimonster

Equal Opportunity in Online Classification with Partial Feedback

https://github.com/saitcakmak/contextual_rs

Bayesian Optimization of Risk Measures

https://github.com/ssedai026/uncertainty-segmentation

Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning

https://github.com/stevenkleinegesse/seqbed

Sequential Bayesian Experimental Design for Implicit Models via Mutual Information

https://github.com/tristandeleu/gfn-maxent-rl

Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions

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