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Rotated MNIST

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전체 기법전체 데이터셋

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평가표

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보존된 평가 기록

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코드

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

https://github.com/AMLab-Amsterdam/DIVA

공식 코드

DIVA: Domain Invariant Variational Autoencoders

https://github.com/andrea-perin/gpsymm

공식 코드

On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory

https://github.com/daniilidis-group/polar-transformer-networks

공식 코드

Polar Transformer Networks

https://github.com/david-knigge/separable-group-convolutional-networks

공식 코드

Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups

https://github.com/gudovskiy/contextflow

공식 코드

ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context Encoding

https://github.com/jaspreetsinghmaan/g-cnn-orims

공식 코드

Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments

https://github.com/m-j-tilley/LXDG

공식 코드

Artificial Neuronal Ensembles with Learned Context Dependent Gating

https://github.com/manosth/cyclical_groups

공식 코드

Learning unfolded networks with a cyclic group structure

https://github.com/mcrl/CyCNN

공식 코드

CyCNN: A Rotation Invariant CNN using Polar Mapping and Cylindrical Convolution Layers

https://github.com/merlresearch/partial_gcnn

공식 코드

Learning Partial Equivariances from Data

https://github.com/microljy/DREN_Tensorflow

공식 코드

Deep Rotation Equivariant Network

https://github.com/microsoft/robustdg

공식 코드

Domain Generalization using Causal Matching

https://github.com/raeidsaqur/CapsGAN

공식 코드

CapsGAN: Using Dynamic Routing for Generative Adversarial Networks

https://github.com/shenzy08/PDO-eConvs

공식 코드

PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions

https://github.com/vihari/csd

공식 코드

Efficient Domain Generalization via Common-Specific Low-Rank Decomposition

https://github.com/AMLab-Amsterdam/DataAugmentationInterventions

DIVA: Domain Invariant Variational Autoencoders

https://github.com/MindSpore-paper-code-3/code8/tree/main/csd

Efficient Domain Generalization via Common-Specific Low-Rank Decomposition

https://github.com/QUVA-Lab/e2cnn

https://github.com/Roderickzzc/Pdo-econv-pytorch

PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions

https://github.com/adambielski/pytorch-gconv-experiments

Group Equivariant Convolutional Networks

https://github.com/deepshwang/swn_gcn

Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network

https://github.com/deepshwang/wn_gcn

Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional Network

https://github.com/deworrall92/harmonicConvolutions

Harmonic Networks: Deep Translation and Rotation Equivariance

https://github.com/ejnnr/steerable_pdo_experiments

PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions

https://github.com/fzw97/GraphDA

DIVA: Domain Invariant Variational Autoencoders

https://github.com/microljy/DREN

Deep Rotation Equivariant Network

https://github.com/rynewu224/graphda

DIVA: Domain Invariant Variational Autoencoders

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