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ORCIDKonstantin Schürholt
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2020 – today
- 2025
[j1]Konstantin Schürholt, Léo Meynent, Yefan Zhou, Haiquan Lu, Yaoqing Yang, Damian Borth:
A Model Zoo on Phase Transitions in Neural Networks. J. Data-centric Mach. Learn. Res. 2: (25):1-34 (2025)- [c9]Zhiyuan Liang, Dongwen Tang, Yuhao Zhou, Xuanlei Zhao, Mingjia Shi, Wangbo Zhao, Zekai Li, Peihao Wang, Konstantin Schürholt, Damian Borth, Michael M. Bronstein, Yang You, Zhangyang (Atlas) Wang, Kai Wang:
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights. NeurIPS 2025 - [c8]Kai Wang, Dongwen Tang, Wangbo Zhao, Konstantin Schürholt, Zhangyang (Atlas) Wang, Yang You:
Scaling Up Parameter Generation: A Recurrent Diffusion Approach. NeurIPS 2025 - [i19]Léo Meynent, Ivan Melev, Konstantin Schürholt, Göran Kauermann, Damian Borth:
Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction. CoRR abs/2503.17138 (2025) - [i18]Damian Falk, Konstantin Schürholt, Damian Borth:
The Impact of Model Zoo Size and Composition on Weight Space Learning. CoRR abs/2504.10141 (2025) - [i17]Damian Falk, Léo Meynent, Florence Pfammatter, Konstantin Schürholt, Damian Borth:
A Model Zoo of Vision Transformers. CoRR abs/2504.10231 (2025) - [i16]Konstantin Schürholt, Léo Meynent, Yefan Zhou, Haiquan Lu, Yaoqing Yang, Damian Borth:
A Model Zoo on Phase Transitions in Neural Networks. CoRR abs/2504.18072 (2025) - [i15]Zhiyuan Liang, Dongwen Tang, Yuhao Zhou, Xuanlei Zhao, Mingjia Shi, Wangbo Zhao, Zekai Li, Peihao Wang, Konstantin Schürholt, Damian Borth, Michael M. Bronstein, Yang You, Zhangyang Wang, Kai Wang:
Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights. CoRR abs/2506.16406 (2025) - [i14]Damian Falk, Konstantin Schürholt, Konstantinos Tzevelekakis, Léo Meynent, Damian Borth:
Learning Model Representations Using Publicly Available Model Hubs. CoRR abs/2510.02096 (2025) - 2024
- [c7]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. GRaM 2024: 146-157 - [c6]Konstantin Schürholt, Michael W. Mahoney, Damian Borth:
Towards Scalable and Versatile Weight Space Learning. ICML 2024: 43947-43966 - [c5]Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang:
MD tree: a model-diagnostic tree grown on loss landscape. ICML 2024: 61825-61853 - [i13]Konstantin Schürholt, Michael W. Mahoney, Damian Borth:
Towards Scalable and Versatile Weight Space Learning. CoRR abs/2406.09997 (2024) - [i12]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) - [i11]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) - [i10]Konstantin Schürholt:
Hyper-Representations: Learning from Populations of Neural Networks. CoRR abs/2410.05107 (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)
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