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teaching:ss2025:dl-equi-dynam [2025/05/29 20:21]
Karnik Ram |
teaching:ss2025:dl-equi-dynam [2025/08/16 10:52] (current)
Karnik Ram Add presentations |
| <td><a href="https://arxiv.org/abs/1602.07576">Group Equivariant Convolutional Networks</a></td> | <td><a href="https://arxiv.org/abs/1602.07576">Group Equivariant Convolutional Networks</a></td> |
| <td>Iñaky</td> | <td>Iñaky</td> |
| <td rowspan="2" style="vertical-align: top;"></td> | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/g-cnn_inaky.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| </a></td> | </a></td> |
| <td>Omar</td> | <td>Omar</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/se3transformer_omar.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/1802.08219">Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds</a></td> | <td><a href="https://arxiv.org/abs/1802.08219">Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds</a></td> |
| <td>Gleb</td> | <td>Gleb</td> |
| <td rowspan="2" style="vertical-align: top;"></td> | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/tfn_gleb.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2211.06489">Equivariance with Learned Canonicalization Functions</a></td> | <td><a href="https://arxiv.org/abs/2211.06489">Equivariance with Learned Canonicalization Functions</a></td> |
| <td>Gianluca</td> | <td>Gianluca</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/canonical_gianluca.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2206.14331">Spherical Channels for Modeling Atomic Interactions</a></td> | <td><a href="https://arxiv.org/abs/2206.14331">Spherical Channels for Modeling Atomic Interactions</a></td> |
| <td>Jean-Pasqual</td> | <td>Jean-Pasqual</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/scn_jean.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/1806.07366">Neural Ordinary Differential Equations</a></td> | <td><a href="https://arxiv.org/abs/1806.07366">Neural Ordinary Differential Equations</a></td> |
| <td>Yaxuan</td> | <td>Yaxuan</td> |
| <td rowspan="2" style="vertical-align: top;"></td> | |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2404.10024">ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs</a></td> | <td><a href="https://arxiv.org/abs/2404.10024">ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs</a></td> |
| <td>Aditi</td> | <td>Aditi</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/climode_aditi.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2405.12868">Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics</a></td> | <td><a href="https://arxiv.org/abs/2405.12868">Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics</a></td> |
| <td>Celia</td> | <td>Celia</td> |
| <td rowspan="2" style="vertical-align: top;"></td> | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/spatio_celia.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2209.14855">Continuous PDE Dynamics Forecasting with Implicit Neural Representations</a></td> | <td><a href="https://arxiv.org/abs/2209.14855">Continuous PDE Dynamics Forecasting with Implicit Neural Representations</a></td> |
| <td>Clemens</td> | <td>Clemens</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ss2025/dl-equi-dynam/dino_clemens.pdf">Slides</a></td> |
| </tr> | </tr> |
| </tbody> | </tbody> |
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