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3D Face Modelling

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코드

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

https://github.com/nicolinho/acc

공식 코드

Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning

https://github.com/nnaisense/MAGE

공식 코드

How to Learn a Useful Critic? Model-based Action-Gradient-Estimator Policy Optimization

https://github.com/nnaisense/pgpelib

공식 코드

ClipUp: A Simple and Powerful Optimizer for Distribution-based Policy Evolution

https://github.com/noc-lab/sac-expert

공식 코드

A Model-Based Approach for Improving Reinforcement Learning Efficiency Leveraging Expert Observations

https://github.com/noetits/ICE-Talk

공식 코드

Analysis and Assessment of Controllability of an Expressive Deep Learning-based TTS system

https://github.com/npu-rcir/online_ccm

공식 코드

Enhanced Robust Tracking Control: An Online Learning Approach

https://github.com/ntavanhoeffelen/daif_carracing

공식 코드

Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem

https://github.com/oh-lab/APPO

공식 코드

Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning

https://github.com/oist-cnru/ReMASTER

공식 코드

Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks

https://github.com/openai/baselines

공식 코드

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

https://github.com/oxwhirl/loaded-dice

공식 코드

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning

https://github.com/papercode2022/hill

공식 코드

Balancing Exploration and Exploitation in Hierarchical Reinforcement Learning via Latent Landmark Graphs

https://github.com/pemami4911/deep-rl

공식 코드

Deep Reinforcement Learning with Feedback-based Exploration

https://github.com/penglingwei/generative-actor-critic

공식 코드

Generative Actor-Critic: An Off-policy Algorithm Using the Push-forward Model

https://github.com/perrin-isir/afu

공식 코드

AFU: Actor-Free critic Updates in off-policy RL for continuous control

https://github.com/pfnet-research/capg

공식 코드

Clipped Action Policy Gradient

https://github.com/pmineiro/smoothcb

공식 코드

Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces

https://github.com/pnnl/deps_arXiv2020

공식 코드

Learning Constrained Adaptive Differentiable Predictive Control Policies With Guarantees

https://github.com/pnnl/neuromancer

공식 코드

Learning Constrained Adaptive Differentiable Predictive Control Policies With Guarantees

https://github.com/ppocma/ppocma

공식 코드

PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation

https://github.com/premiertaco/premier-taco

공식 코드

Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss

https://github.com/purewater0901/BSMPC

공식 코드

Bisimulation metric for Model Predictive Control

https://github.com/puyuan1996/LC-SAC

공식 코드

Context-Based Soft Actor Critic for Environments with Non-stationary Dynamics

https://github.com/qiujumin/don-rl

공식 코드

Decision-making and control with diffractive optical networks

https://github.com/qlan3/Explorer

공식 코드

Model-free Policy Learning with Reward Gradients

https://github.com/qlan3/quantumexplorer

공식 코드

Variational Quantum Soft Actor-Critic

https://github.com/qutrobotlearning/batchlearning

공식 코드

Evaluating task-agnostic exploration for fixed-batch learning of arbitrary future tasks

https://github.com/ravikt/gril

공식 코드

Imitation Learning with Human Eye Gaze via Multi-Objective Prediction

https://github.com/rcheng805/CORE-RL

공식 코드

Control Regularization for Reduced Variance Reinforcement Learning

https://github.com/rddy/pico

공식 코드

Pragmatic Image Compression for Human-in-the-Loop Decision-Making

https://github.com/resibots/blackdrops

공식 코드

Black-Box Data-efficient Policy Search for Robotics

https://github.com/resibots/kaushik_2018_multi-dex

공식 코드

Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards

https://github.com/rickyang2016/bayesian-soft-actor-critic--bsac

공식 코드

Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning

https://github.com/ringbdstack/sisa

공식 코드

Hierarchical State Abstraction Based on Structural Information Principles

https://github.com/rinuboney/fpac

공식 코드

Learning of feature points without additional supervision improves reinforcement learning from images

https://github.com/rinuboney/keyq

공식 코드

Learning of feature points without additional supervision improves reinforcement learning from images

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