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Value prediction

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코드

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

https://github.com/Hwhitetooth/random_gvfs

공식 코드

Learning State Representations from Random Deep Action-conditional Predictions

https://github.com/ShangtongZhang/DeepRL

공식 코드

ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search

https://github.com/black-yt/ExtremeCast

공식 코드

ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast

https://github.com/demon702/worldvaluesbench

공식 코드

WorldValuesBench: A Large-Scale Benchmark Dataset for Multi-Cultural Value Awareness of Language Models

https://github.com/dibyaghosh/icvf_release

공식 코드

Reinforcement Learning from Passive Data via Latent Intentions

https://github.com/elisim/piven

공식 코드

PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction

https://github.com/frankhlchi/infer_data_valuation

공식 코드

Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation

https://github.com/jimmyyhwu/spatial-action-maps

공식 코드

Spatial Action Maps for Mobile Manipulation

https://github.com/junhyukoh/value-prediction-network

공식 코드

Value Prediction Network

https://github.com/loadingbyte/timexplain

공식 코드

timeXplain -- A Framework for Explaining the Predictions of Time Series Classifiers

https://github.com/mtics/feddae

공식 코드

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach

https://github.com/oxwhirl/treeqn

공식 코드

TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning

https://github.com/stilwell-git/doubly-bounded-q-learning

공식 코드

On the Estimation Bias in Double Q-Learning

https://github.com/sttdanonymous/sttd

공식 코드

Uncertainty-Aware Probabilistic Graph Neural Networks for Road-Level Traffic Accident Prediction

https://github.com/sunxiaojie99/mural

공식 코드

A Multi-Granularity-Aware Aspect Learning Model for Multi-Aspect Dense Retrieval

https://github.com/tanchongmin/learning-fast-and-slow

공식 코드

Learning, Fast and Slow: A Goal-Directed Memory-Based Approach for Dynamic Environments

https://github.com/thuml/CompilerDream

공식 코드

CompilerDream: Learning a Compiler World Model for General Code Optimization

https://github.com/xmed-lab/sdaof

공식 코드

Spatial-Division Augmented Occupancy Field for Bone Shape Reconstruction from Biplanar X-Rays

https://github.com/corl-team/CORL

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

https://github.com/geohot/twitchcoq

Value Prediction Network

https://github.com/howuhh/sac-n-jax

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

https://github.com/palevas/syntax-score-prediction

CardioSyntax: end-to-end SYNTAX score prediction -- dataset, benchmark and method

https://github.com/snu-mllab/edac

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

https://github.com/yihaosun1124/OfflineRL-Kit

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

https://github.com/zzmtsvv/rl_task

Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble

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