| Learning Invariant Representations for Equivariant Neural Networks Using Orthogonal Moments | Sep 22, 2022 | Rotated MNISTTranslation | CodeCode Available | 0 |
| Diversity Boosted Learning for Domain Generalization with Large Number of Domains | Jul 28, 2022 | DiversityDomain Generalization | —Unverified | 0 |
| Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge | Jul 11, 2022 | Domain GeneralizationRotated MNIST | —Unverified | 0 |
| Transform-Invariant Convolutional Neural Networks for Image Classification and Search | Jun 18, 2022 | Classificationimage-classification | —Unverified | 0 |
| Improving the Sample-Complexity of Deep Classification Networks with Invariant Integration | Feb 8, 2022 | Rotated MNIST | —Unverified | 0 |
| Learning Augmentation Distributions using Transformed Risk Minimization | Nov 16, 2021 | Rotated MNIST | —Unverified | 0 |
| Learning Rotation Invariant Features for Cryogenic Electron Microscopy Image Reconstruction | Jan 10, 2021 | ClusteringDecoder | —Unverified | 0 |
| Invariant Integration in Deep Convolutional Feature Space | Apr 20, 2020 | Rotated MNIST | —Unverified | 0 |
| VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing | Jan 1, 2020 | ColorizationCompressive Sensing | CodeCode Available | 0 |
| Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data | Nov 18, 2019 | Object RecognitionRotated MNIST | —Unverified | 0 |
