Papers with Code 아카이브
Tomography
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/chungentsai/mlqst
공식 코드Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
https://github.com/chungentsai/pip
공식 코드Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
https://github.com/cicwi/recast3d
공식 코드https://github.com/haimengzhao/bounded-gate-tomography
공식 코드Learning quantum states and unitaries of bounded gate complexity
https://github.com/jakeoung/ShapeFromProjections
공식 코드Shape from Projections via Differentiable Forward Projector for Computed Tomography
https://github.com/jindi0/more
공식 코드MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classification
https://github.com/kamil-safin/SCFW
공식 코드https://github.com/mli-lab/deepdewedge
공식 코드https://github.com/netket/netket
공식 코드NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems
https://github.com/nirajmg/fibsem_segmentation
공식 코드Deep learning-based identification of sub-nuclear structures in FIB-SEM images
https://github.com/quantshah/qst-cgan
공식 코드Quantum State Tomography with Conditional Generative Adversarial Networks
https://github.com/quantshah/qst-nn
공식 코드Classification and reconstruction of optical quantum states with deep neural networks
https://github.com/swing-research/cryolithe
공식 코드https://github.com/swing-research/implicit-cryo-electron-tomography
공식 코드Ice-Tide: Implicit Cryo-ET Imaging and Deformation Estimation
https://github.com/xulabs/aitom
공식 코드AITom: Open-source AI platform for cryo-electron tomography data analysis
https://github.com/yu4u/kaggle-czii-4th
공식 코드2.5D U-Net with Depth Reduction for 3D CryoET Object Identification
https://github.com/bio-phys/BioEM
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images
https://github.com/iisharankov/QuantumStateTomography
https://github.com/pythonLoader/Aitom_COVID-19
AITom: Open-source AI platform for cryo-electron tomography data analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.