| Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs | 0 | 0.34 | 2021 |
| Skip-Convolutions for Efficient Video Processing | 0 | 0.34 | 2021 |
| Overfitting for Fun and Profit: Instance-Adaptive Data Compression | 0 | 0.34 | 2021 |
| Teacher–Student Curriculum Learning | 8 | 0.46 | 2020 |
| Natural Graph Networks | 0 | 0.34 | 2020 |
| Lossy Compression with Distortion Constrained Optimization | 0 | 0.34 | 2020 |
| Adversarial Distortion for Learned Video Compression | 0 | 0.34 | 2020 |
| Feedback Recurrent Autoencoder for Video Compression. | 0 | 0.34 | 2020 |
| Parallelized Rate-Distortion Optimized Quantization Using Deep Learning | 0 | 0.34 | 2020 |
| Pulmonary nodule detection in CT scans with equivariant CNNs. | 5 | 0.46 | 2019 |
| Covariance in Physics and Convolutional Neural Networks. | 0 | 0.34 | 2019 |
| Gauge Equivariant Convolutional Networks and the Icosahedral CNN. | 7 | 0.45 | 2019 |
| Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks. | 0 | 0.34 | 2018 |
| 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data. | 7 | 0.59 | 2018 |
| A General Theory of Equivariant CNNs on Homogeneous Spaces | 2 | 0.36 | 2018 |
| HexaConv. | 0 | 0.34 | 2018 |
| Spherical CNNs. | 0 | 0.34 | 2018 |
| Explorations in Homeomorphic Variational Auto-Encoding. | 2 | 0.37 | 2018 |
| Rotation Equivariant CNNs for Digital Pathology. | 8 | 0.54 | 2018 |
| Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks). | 3 | 0.48 | 2018 |
| Interpretation of microbiota-based diagnostics by explaining individual classifier decisions. | 2 | 0.36 | 2017 |
| Convolutional Networks for Spherical Signals. | 3 | 0.38 | 2017 |
| Steerable CNNs. | 0 | 0.34 | 2017 |
| Visualizing Deep Neural Network Decisions: Prediction Difference Analysis. | 50 | 2.03 | 2017 |
| Group Equivariant Convolutional Networks. | 83 | 3.08 | 2016 |
| Harmonic Exponential Families on Manifolds | 4 | 0.74 | 2015 |
| Transformation Properties of Learned Visual Representations. | 25 | 1.64 | 2014 |
| Learning the Irreducible Representations of Commutative Lie Groups. | 19 | 1.50 | 2014 |
