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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/SkyWa7ch3r/ImageSegmentation

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://github.com/SkyWa7ch3r/SceneSegmentation

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://github.com/Stanford-ILIAD/Learn-Imperfect-Varying-Dynamics

Learning from Imperfect Demonstrations from Agents with Varying Dynamics

https://github.com/StanfordASL/SCOD

Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks

https://github.com/StanfordVL/iGibson

IGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenes

https://github.com/StanfordVL/iGibsonChallenge2021

IGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenes

https://github.com/Steinheilig/Imbiss

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/Stsh4lson/TOM-2020

The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

https://github.com/Suryavf/SelfDrivingCar

End-to-end Driving via Conditional Imitation Learning

https://github.com/TQCAI/graph_nets_pytorch

Relational inductive biases, deep learning, and graph networks

https://github.com/TTL30/PPE-Deep-Distribituion-Regression

Deep Distribution Regression

https://github.com/TeamSAIDA/SAIDA

Clear the Fog: Combat Value Assessment in Incomplete Information Games with Convolutional Encoder-Decoders

https://github.com/Techget/gail-tf-sc2

Generative Adversarial Imitation Learning

https://github.com/TianxingChen/RoboTwin

G3Flow: Generative 3D Semantic Flow for Pose-aware and Generalizable Object Manipulation

https://github.com/TianyueChu/FedQV

FedQV: Leveraging Quadratic Voting in Federated Learning

https://github.com/TimoSaemann/caffe-segnet-cudnn5

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://github.com/Tinker-Twins/Behavioral-Cloning-Simulator

Robust Behavioral Cloning for Autonomous Vehicles using End-to-End Imitation Learning

https://github.com/TqDavid/td

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

https://github.com/TrentBrick/RewardConditionedUDRL

Reward-Conditioned Policies

https://github.com/TrustworthyAI-kr/LFI-CAM

LFI-CAM: Learning Feature Importance for Better Visual Explanation

https://github.com/UnibucProjects/DeepRLRecommenderSystem

Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application

https://github.com/Usman-Rafique/Probabilistic_UNet

A Probabilistic U-Net for Segmentation of Ambiguous Images

https://github.com/VictorBoutin/InteractionMap

Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system

https://github.com/VinAIResearch/PCC-pytorch

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control

https://github.com/VirgiAgl/DAG-GP

Multi-task Causal Learning with Gaussian Processes

https://github.com/WuJie1010/Temporally-language-grounding

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

https://github.com/X3N4/car_racer

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/XanaduAI/pennylane

Better than classical? The subtle art of benchmarking quantum machine learning models

https://github.com/Xi-Liu/heteroscedasticbandits

Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging

https://github.com/XuehaiPan/Soft-Actor-Critic

Soft Actor-Critic Algorithms and Applications

https://github.com/YadiLao/MM-Tag

A Tree Search Algorithm for Sequence Labeling

https://github.com/YanjieZe/Improved-3D-Diffusion-Policy

PointVLA: Injecting the 3D World into Vision-Language-Action Models

https://github.com/YantianZha/Affordance-Aware-Imitation-Learning

Contrastively Learning Visual Attention as Affordance Cues from Demonstrations for Robotic Grasping

https://github.com/YimingXiao98/DamageCAT

Large-scale Building Damage Assessment using a Novel Hierarchical Transformer Architecture on Satellite Images

https://github.com/YingjingLu/FLNN

Not All Features Are Equal: Feature Leveling Deep Neural Networks for Better Interpretation

https://github.com/YuanJianhao508/RAG-Driver

RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Learning in Multi-Modal Large Language Model

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