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teaching:ws2024:dl4science [2024/11/03 12:39]
Karnik Ram |
teaching:ws2024:dl4science [2025/02/06 22:59] (current)
Karnik Ram |
| <td><a href="https://www.nature.com/articles/s41586-021-03819-2">Highly accurate protein structure prediction with AlphaFold 2</a></td> | <td><a href="https://www.nature.com/articles/s41586-021-03819-2">Highly accurate protein structure prediction with AlphaFold 2</a></td> |
| <td>Zeyu</td> | <td>Zeyu</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/zeyu.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2402.04845">AlphaFold Meets Flow Matching for Generating Protein Ensembles</a></td> | <td><a href="https://arxiv.org/abs/2402.04845">AlphaFold Meets Flow Matching for Generating Protein Ensembles</a></td> |
| <td>Sascha</td> | <td>Sascha</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/sascha.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td rowspan="2">Nov 12</td> | <td rowspan="2">Nov 12</td> |
| <td><a href="https://arxiv.org/abs/2312.15796">GenCast: Diffusion-based ensemble forecasting for medium-range weather</a></td> | <td><a href="https://arxiv.org/abs/2312.15796">GenCast: Diffusion-based ensemble forecasting for medium-range weather</a></td> |
| <td>Leonhard</td> | <td>Leonhard<br> <b>Voted best presentation</b></td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/leonhard.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2405.13063">Aurora: A Foundation Model of the Atmosphere</a></td> | <td><a href="https://arxiv.org/abs/2405.13063">Aurora: A Foundation Model of the Atmosphere</a></td> |
| <td>Frederic</td> | <td>Frederic</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/frederic.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://openaccess.thecvf.com/content/CVPR2024/html/Stevens_BioCLIP_A_Vision_Foundation_Model_for_the_Tree_of_Life_CVPR_2024_paper.html">BioCLIP: A Vision Foundation Model for the Tree of Life</a></td> | <td><a href="https://openaccess.thecvf.com/content/CVPR2024/html/Stevens_BioCLIP_A_Vision_Foundation_Model_for_the_Tree_of_Life_CVPR_2024_paper.html">BioCLIP: A Vision Foundation Model for the Tree of Life</a></td> |
| <td>Qianlong</td> | <td>Qianlong</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/xiao.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://openreview.net/forum?id=vN9fpfqoP1">Fine-Tuned Language Models Generate Stable Inorganic Materials as Text</a></td> | <td><a href="https://openreview.net/forum?id=vN9fpfqoP1">Fine-Tuned Language Models Generate Stable Inorganic Materials as Text</a></td> |
| <td>Ahmet</td> | <td>Ahmet</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/ahmet.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://www.nature.com/articles/s41586-023-06735-9">Scaling deep learning for materials discovery</a></td> | <td><a href="https://www.nature.com/articles/s41586-023-06735-9">Scaling deep learning for materials discovery</a></td> |
| <td>Jannis</td> | <td>Jannis</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/jannis.pdf">Slides</a></td> |
| </tr> | </tr> |
| <tr> | <tr> |
| <td><a href="https://arxiv.org/abs/2408.10205">KAN 2.0: Kolmogorov-Arnold Networks Meet Science</a></td> | <td><a href="https://arxiv.org/abs/2408.10205">KAN 2.0: Kolmogorov-Arnold Networks Meet Science</a></td> |
| <td>Jonathan</td> | <td>Jonathan</td> |
| | <td><a href="https://cvg.cit.tum.de/_media/teaching/ws2024/dl4science/jonathan.pdf">Slides</a></td> |
| </tr> | </tr> |
| </table> | </table> |
| == List of potential papers == | == List of potential papers == |
| |
| ^No. ^Paper ^ | |
| | 1 | [[https://openreview.net/forum?id=B73niNjbPs|Continuous PDE Dynamics Forecasting with Implicit Neural Representations]]| | [[https://cvg.cit.tum.de/teaching/ws2024/dl4science/papers | Available here]] |
| | 2 | [[https://arxiv.org/abs/2108.08481|Neural Operator: Learning Maps Between Function Spaces | |
| ]]| | |
| | 3 | [[https://arxiv.org/abs/2401.11037|Equivariant Graph Neural Operator for Modeling 3D Dynamics | |
| ]]| | |
| | 4 | [[https://www.nature.com/articles/s41467-022-29939-5|E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials]]| | |
| | 5 | [[https://www.nature.com/articles/s41467-023-36329-y|Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics | |
| ]] | | |
| | 6 | [[https://arxiv.org/abs/2210.06662|Action Matching: Learning Stochastic Dynamics from Samples | |
| ]] | | |
| | 7 | [[https://openreview.net/forum?id=xuY33XhEGR|ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs]]| | |
| | 8 | [[https://arxiv.org/abs/2312.15796|GenCast: Diffusion-based ensemble forecasting for medium-range weather | |
| ]] | | |
| | 9 | [[https://arxiv.org/abs/2405.13063|Aurora: A Foundation Model of the Atmosphere | |
| ]]| | |
| | 10 | [[https://openreview.net/forum?id=vN9fpfqoP1|Fine-Tuned Language Models Generate Stable Inorganic Materials as Text]]| | |
| | 11 | [[https://openreview.net/forum?id=W4pB7VbzZI|FlowMM: Generating Materials with Riemannian Flow Matching]]| | |
| | 12 | [[https://openreview.net/forum?id=5Z3GURcqwT|Spherical Channels for Modeling Atomic Interactions]]| | |
| | 13 | [[https://arxiv.org/abs/2312.03687|MatterGen: a generative model for inorganic materials design]]| | |
| | 14| [[https://arxiv.org/abs/2405.04967|MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures]] | | |
| | 15 | [[https://www.nature.com/articles/s41586-023-06735-9|Scaling deep learning for materials discovery | |
| ]] | | |
| | 16 | [[https://www.nature.com/articles/s41586-021-03819-2|Highly accurate protein structure prediction with AlphaFold 2]] | | |
| | 17 | [[https://www.nature.com/articles/s41586-024-07487-w|Accurate structure prediction of biomolecular interactions with AlphaFold 3]] | | |
| | 18 | [[https://openreview.net/forum?id=kKF8_K-mBbS|DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking]]| | |
| | 19 | [[https://openreview.net/forum?id=yQcebEgQfH|AlphaFold Meets Flow Matching for Generating Protein Ensembles | |
| ]]| | |
| | 20 | [[https://arxiv.org/abs/2106.12594|Real-time gravitational-wave science with neural posterior estimation]]| | |
| | 21 | [[https://arxiv.org/abs/2404.09636|All-in-one simulation-based inference]] | | |
| | 22 | [[https://arxiv.org/abs/2306.11925|LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching]]| | |
| | 23 | [[https://openaccess.thecvf.com/content/CVPR2024/html/Stevens_BioCLIP_A_Vision_Foundation_Model_for_the_Tree_of_Life_CVPR_2024_paper.html|BioCLIP: A Vision Foundation Model for the Tree of Life]]| | |
| | 24 | [[https://arxiv.org/abs/2408.10205|KAN 2.0: Kolmogorov-Arnold Networks Meet Science | |
| ]] | | |
| | 25 | [[https://arxiv.org/abs/2006.11287|Discovering Symbolic Models from Deep Learning with Inductive Biases | |
| ]] | | |
| | 26 | [[https://openreview.net/forum?id=vJx6fld6l0|Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics]] | | |
| |
| == Additional Resources == | == Additional Resources == |
| * [[https://arxiv.org/abs/2312.07511|A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems | * [[https://arxiv.org/abs/2312.07511|A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems |
| ]] | ]] |
| * [[https://cvg.cit.tum.de/teaching/ss2024/dl4science| Previous offering of seminar]] | * [[https://cvg.cit.tum.de/teaching/ss2024/dl4science| Deep learning for the natural sciences SS2024]] |
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