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Konstantin Schürholt
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2020 – today
- 2024
- [c6]Konstantin Schürholt, Michael W. Mahoney, Damian Borth:
Towards Scalable and Versatile Weight Space Learning. ICML 2024 - [c5]Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang:
MD tree: a model-diagnostic tree grown on loss landscape. ICML 2024 - [i12]Konstantin Schürholt, Michael W. Mahoney, Damian Borth:
Towards Scalable and Versatile Weight Space Learning. CoRR abs/2406.09997 (2024) - [i11]Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang:
MD tree: a model-diagnostic tree grown on loss landscape. CoRR abs/2406.16988 (2024) - [i10]Christian Nauck, Rohan Gorantla, Michael Lindner, Konstantin Schürholt, Antonia S. J. S. Mey, Frank Hellmann:
Dirac-Bianconi Graph Neural Networks - Enabling Non-Diffusive Long-Range Graph Predictions. CoRR abs/2407.12419 (2024) - 2023
- [c4]Dominik Honegger, Konstantin Schürholt, Linus Scheibenreif, Damian Borth:
Eurosat Model Zoo: A Dataset and Benchmark on Populations of Neural Networks and Its Sparsified Model Twins. IGARSS 2023: 888-891 - [i9]Dominik Honegger, Konstantin Schürholt, Damian Borth:
Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models. CoRR abs/2304.13718 (2023) - 2022
- [c3]Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth:
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. NeurIPS 2022 - [c2]Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth:
Model Zoos: A Dataset of Diverse Populations of Neural Network Models. NeurIPS 2022 - [i8]Christian Nauck, Michael Lindner, Konstantin Schürholt, Frank Hellmann:
Dynamic stability of power grids - new datasets for Graph Neural Networks. CoRR abs/2206.06369 (2022) - [i7]Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth:
Hyper-Representations for Pre-Training and Transfer Learning. CoRR abs/2207.10951 (2022) - [i6]Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth:
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. CoRR abs/2209.14733 (2022) - [i5]Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth:
Model Zoos: A Dataset of Diverse Populations of Neural Network Models. CoRR abs/2209.14764 (2022) - [i4]Christian Nauck, Michael Lindner, Konstantin Schürholt, Frank Hellmann:
Towards dynamic stability analysis of sustainable power grids using graph neural networks. CoRR abs/2212.11130 (2022) - 2021
- [c1]Konstantin Schürholt, Dimche Kostadinov, Damian Borth:
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction. NeurIPS 2021: 16481-16493 - [i3]Christian Nauck, Michael Lindner, Konstantin Schürholt, Haoming Zhang, Paul Schultz, Jürgen Kurths, Ingrid Isenhardt, Frank Hellmann:
Predicting Dynamic Stability of Power Grids using Graph Neural Networks. CoRR abs/2108.08230 (2021) - [i2]Konstantin Schürholt, Dimche Kostadinov, Damian Borth:
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction. CoRR abs/2110.15288 (2021) - 2020
- [i1]Konstantin Schürholt, Damian Borth:
An Investigation of the Weight Space for Version Control of Neural Networks. CoRR abs/2006.10424 (2020)
Coauthor Index
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last updated on 2024-09-04 00:30 CEST by the dblp team
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