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Friction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

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

https://github.com/mizolotu/SmartExcavator

Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards

https://github.com/mohammeddonia/RSCAM-GradNoise

Stochastic Gradient Hamiltonian Monte Carlo

https://github.com/nhadidi/splashnet

emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography

https://github.com/prip-lab/MSU-LatentAFIS

Automatic Latent Fingerprint Segmentation

https://github.com/rocm/tensorcast

Microscaling Data Formats for Deep Learning

https://github.com/sanweiliti/lemo

Learning Motion Priors for 4D Human Body Capture in 3D Scenes

https://github.com/sjtuzq/Cycle_Dynamics

Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency

https://github.com/soran-ghaderi/torchebm

Stochastic Gradient Hamiltonian Monte Carlo

https://github.com/sureli/rrls

Robust Adversarial Reinforcement Learning

https://github.com/vincentyu68/policy_transfer

Preparing for the Unknown: Learning a Universal Policy with Online System Identification

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