SOTAVerified

Rotated MNIST

Papers

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Showing 1–41 of 41 papers

TitleStatusHype
General E(2)-Equivariant Steerable CNNsCode1
Exploiting Redundancy: Separable Group Convolutional Networks on Lie GroupsCode1
Domain Generalization using Causal MatchingCode1
Efficient Domain Generalization via Common-Specific Low-Rank DecompositionCode1
Equivariance-bridged SO(2)-Invariant Representation Learning using Graph Convolutional NetworkCode1
PDO-eConvs: Partial Differential Operator Based Equivariant ConvolutionsCode1
CyCNN: A Rotation Invariant CNN using Polar Mapping and Cylindrical Convolution LayersCode1
Learning Partial Equivariances from DataCode1
Harmonic Networks: Deep Translation and Rotation EquivarianceCode1
DIVA: Domain Invariant Variational AutoencodersCode1
Learning unfolded networks with a cyclic group structureCode0
Artificial Neuronal Ensembles with Learned Context Dependent GatingCode0
CapsGAN: Using Dynamic Routing for Generative Adversarial NetworksCode0
ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context EncodingCode0
Deep Rotation Equivariant NetworkCode0
Group Equivariant Convolutional NetworksCode0
Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal MomentsCode0
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel TheoryCode0
Polar Transformer NetworksCode0
VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video ProcessingCode0
Scale-Rotation-Equivariant Lie Group Convolution Neural Networks (Lie Group-CNNs)—0
Group Invariant Global Pooling—0
Deformable Classifiers—0
ICNN: INPUT-CONDITIONED FEATURE REPRESENTATION LEARNING FOR TRANSFORMATION-INVARIANT NEURAL NETWORK—0
Improving the Sample-Complexity of Deep Classification Networks with Invariant Integration—0
Invariant Integration in Deep Convolutional Feature Space—0
Learning Augmentation Distributions using Transformed Risk Minimization—0
Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data—0
Transform-Invariant Convolutional Neural Networks for Image Classification and Search—0
Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction—0
Learning Steerable Filters for Rotation Equivariant CNNs—0
Local Group Invariant Representations via Orbit Embeddings—0
Unsupervised discovery of the shared and private geometry in multi-view data—0
What's Inside Your Diffusion Model? A Score-Based Riemannian Metric to Explore the Data Manifold—0
Visual Context-aware Convolution Filters for Transformation-invariant Neural Network—0
Progressive Conservative Adaptation for Evolving Target Domains—0
Diversity Boosted Learning for Domain Generalization with Large Number of Domains—0
Fast Inference in Capsule Networks Using Accumulated Routing Coefficients—0
GDO: Gradual Domain Osmosis—0
DIVA: Domain Invariant Variational Autoencoder—0
Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Steerable Filter CNNTest error0.71—Unverified
2E2FCNN (D16 |5 C16)Test error0.68—Unverified
3Sim2-CNNTest error0.59—Unverified