Papers with Code 아카이브

Robust Design

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

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

https://github.com/Data-Science-in-Mechanical-Engineering/prlqr

공식 코드

Probabilistic Robust Linear Quadratic Regulators with Gaussian Processes

https://github.com/LorenzoFederici/RobustTrajectoryDesignbyRL

공식 코드

Reinforcement Learning for Low-Thrust Trajectory Design of Interplanetary Missions

https://github.com/Waasem/RobDanns

공식 코드

Exploring Robust Architectures for Deep Artificial Neural Networks

https://github.com/alibaba/easyrobust

공식 코드

Towards Robust Vision Transformer

https://github.com/bensonren/aem_dim_bench

공식 코드

Inverse deep learning methods and benchmarks for artificial electromagnetic material design

https://github.com/canbooo/duqo

공식 코드

Local Latin Hypercube Refinement for Multi-objective Design Uncertainty Optimization

https://github.com/idm-uwb/fusion2024_sif

공식 코드

Stochastic Integration Based Estimator: Robust Design and Stone Soup Implementation

https://github.com/peterdsharpe/neuralfoil

공식 코드

NeuralFoil: An Airfoil Aerodynamics Analysis Tool Using Physics-Informed Machine Learning

https://github.com/spratm-asleaf/robust-waveform

공식 코드

Robust Waveform Design for Integrated Sensing and Communication

https://github.com/thyrixyang/rid-noise-aaai22

공식 코드

RID-Noise: Towards Robust Inverse Design under Noisy Environments

https://github.com/vtddggg/Robust-Vision-Transformer

공식 코드

Towards Robust Vision Transformer

https://github.com/wchen459/gan-duf

공식 코드

GAN-DUF: Hierarchical Deep Generative Models for Design Under Free-Form Geometric Uncertainty

https://github.com/ArashRahnama/RobustLyapunovDNNs

Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory

https://github.com/akiratosei/neulag

Inverse deep learning methods and benchmarks for artificial electromagnetic material design

https://github.com/charlesjin/emergent-semantics

Latent Causal Probing: A Formal Perspective on Probing with Causal Models of Data

https://github.com/jacquesboitreaud/optimol

Conditioning by adaptive sampling for robust design

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