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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/snu-mllab/EMI

공식 코드

EMI: Exploration with Mutual Information

https://github.com/soanagno/wakenet

공식 코드

Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models

https://github.com/soltoggio/ct-graph

공식 코드

Context Meta-Reinforcement Learning via Neuromodulation

https://github.com/spiglerg/sb3_distill

공식 코드

Proximal Policy Distillation

https://github.com/spotify-research/il-by-rl

공식 코드

Imitation Learning by Reinforcement Learning

https://github.com/srsohn/shortest-path-rl

공식 코드

Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks

https://github.com/stanford-iliad/ileed

공식 코드

Imitation Learning by Estimating Expertise of Demonstrators

https://github.com/stanfordai4hi/poela

공식 코드

Offline Policy Optimization with Eligible Actions

https://github.com/stepjam/ARM

공식 코드

Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisation

https://github.com/stepjam/BPP

공식 코드

Bingham Policy Parameterization for 3D Rotations in Reinforcement Learning

https://github.com/sureli/rrls

공식 코드

RRLS : Robust Reinforcement Learning Suite

https://github.com/sweetice/beer-iclr2024

공식 코드

Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation

https://github.com/tajwarfahim/proactive_interventions

공식 코드

When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning

https://github.com/taowang0/value-estimation-vpg

공식 코드

Improving Value Estimation Critically Enhances Vanilla Policy Gradient

https://github.com/tbasaklar/PDMORL-Preference-Driven-Multi-Objective-Reinforcement-Learning-Algorithm

공식 코드

PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm

https://github.com/tedmoskovitz/DOPE

공식 코드

Tactical Optimism and Pessimism for Deep Reinforcement Learning

https://github.com/tedmoskovitz/TOP

공식 코드

Tactical Optimism and Pessimism for Deep Reinforcement Learning

https://github.com/tensorflow/community

공식 코드

TF-Replicator: Distributed Machine Learning for Researchers

https://github.com/tensorflow/models

공식 코드

Trust-PCL: An Off-Policy Trust Region Method for Continuous Control

https://github.com/tesslerc/ActionRobustRL

공식 코드

Action Robust Reinforcement Learning and Applications in Continuous Control

https://github.com/tesslerc/GAC

공식 코드

Distributional Policy Optimization: An Alternative Approach for Continuous Control

https://github.com/tgangwani/BMIL

공식 코드

Learning Belief Representations for Imitation Learning in POMDPs

https://github.com/thanard/me-trpo

공식 코드

Model-Ensemble Trust-Region Policy Optimization

https://github.com/thecharlieblake/snowflake

공식 코드

Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing

https://github.com/thu-ml/efficient-diffusion-alignment

공식 코드

Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control

https://github.com/tianheyu927/mopo

공식 코드

MOPO: Model-based Offline Policy Optimization

https://github.com/tkipf/compile

공식 코드

CompILE: Compositional Imitation Learning and Execution

https://github.com/tnresearch/forlorn

공식 코드

FORLORN: A Framework for Comparing Offline Methods and Reinforcement Learning for Optimization of RAN Parameters

https://github.com/tobiabir/hambo

공식 코드

Hallucinated Adversarial Control for Conservative Offline Policy Evaluation

https://github.com/trevormcinroe/pixelbrax

공식 코드

PixelBrax: Learning Continuous Control from Pixels End-to-End on the GPU

https://github.com/trzhang0116/HRAC

공식 코드

Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning

https://github.com/tseyde/decqn

공식 코드

Solving Continuous Control via Q-learning

https://github.com/tyq1024/rlx2

공식 코드

RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch

https://github.com/ubisoft/directbehaviorspecification

공식 코드

Direct Behavior Specification via Constrained Reinforcement Learning

https://github.com/ugr-sail/sinergym

공식 코드

SINERGYM -- A virtual testbed for building energy optimization with Reinforcement Learning

https://github.com/unstable-zeros/tasil

공식 코드

TaSIL: Taylor Series Imitation Learning

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