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3D Face Modelling

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

https://github.com/adaptive-intelligent-robotics/qdax

공식 코드

QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration

https://github.com/adipandas/gym_multirotor

공식 코드

Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors

https://github.com/adityab/crossq

공식 코드

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity

https://github.com/aidanscannell/dcmpc

공식 코드

Discrete Codebook World Models for Continuous Control

https://github.com/ait-lab/ggtde

공식 코드

Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning

https://github.com/amathislab/dmap

공식 코드

DMAP: a Distributed Morphological Attention Policy for Learning to Locomote with a Changing Body

https://github.com/amazon-research/meta-q-learning

공식 코드

Meta-Q-Learning

https://github.com/amazon-research/replay-based-recurrent-rl

공식 코드

Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges

https://github.com/amazon-science/replay-based-recurrent-rl

공식 코드

Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges

https://github.com/amir-karimi96/continuous-time-continuous-option-policy-gradient

공식 코드

Dynamic Decision Frequency with Continuous Options

https://github.com/anandkamat05/TDEOC

공식 코드

Diversity-Enriched Option-Critic

https://github.com/anndvision/vsop

공식 코드

ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages

https://github.com/anonicml2019/icml_2019_state_abstraction

공식 코드

Learning State Abstractions for Transfer in Continuous Control

https://github.com/anuragranj/coma

공식 코드

Generating 3D faces using Convolutional Mesh Autoencoders

https://github.com/apexrl/coil

공식 코드

Curriculum Offline Imitation Learning

https://github.com/architsharma97/medal

공식 코드

A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning

https://github.com/arpit15/skill-based-exploration-drl

공식 코드

Model Learning for Look-ahead Exploration in Continuous Control

https://github.com/asperti/microracer

공식 코드

MicroRacer: a didactic environment for Deep Reinforcement Learning

https://github.com/atavakol/action-branching-agents

공식 코드

Action Branching Architectures for Deep Reinforcement Learning

https://github.com/atavakol/action-hypergraph-networks

공식 코드

Learning to Represent Action Values as a Hypergraph on the Action Vertices

https://github.com/automl/TempoRL

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TempoRL: Learning When to Act

https://github.com/aviralkumar2907/CQL

공식 코드

Conservative Q-Learning for Offline Reinforcement Learning

https://github.com/awskhalil/oscar

공식 코드

PLM-Net: Perception Latency Mitigation Network for Vision-Based Lateral Control of Autonomous Vehicles

https://github.com/baimingc/dambrl

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Delay-Aware Model-Based Reinforcement Learning for Continuous Control

https://github.com/baitingluo/l-map

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Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction

https://github.com/batra-mlp-lab/va_mbrl

공식 코드

Model-Advantage and Value-Aware Models for Model-Based Reinforcement Learning: Bridging the Gap in Theory and Practice

https://github.com/baturaysaglam/ac-off-poc

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Mitigating Off-Policy Bias in Actor-Critic Methods with One-Step Q-learning: A Novel Correction Approach

https://github.com/baturaysaglam/dase

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Safe and Robust Experience Sharing for Deterministic Policy Gradient Algorithms

https://github.com/baturaysaglam/discover

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Deep Intrinsically Motivated Exploration in Continuous Control

https://github.com/baturaysaglam/la3p

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Actor Prioritized Experience Replay

https://github.com/baturaysaglam/swtd3

공식 코드

Parameter-free Reduction of the Estimation Bias in Deep Reinforcement Learning for Deterministic Policy Gradients

https://github.com/bellmantimehut/dipo

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Policy Representation via Diffusion Probability Model for Reinforcement Learning

https://github.com/bluecontra/AAAI2021-VDFP

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Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction

https://github.com/bmazoure/sparseMuJoCo

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Leveraging exploration in off-policy algorithms via normalizing flows

https://github.com/boschresearch/DD_OPG

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Trajectory-Based Off-Policy Deep Reinforcement Learning

https://github.com/boschresearch/dist-mbrl

공식 코드

Value-Distributional Model-Based Reinforcement Learning

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