Konstantin Schürholt

27 papers A* 5C 1Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Model Zoo of Vision Transformers. CoRR Damian Falk, Léo Meynent, Florence Pfammatter, Konstantin Schürholt, Damian Borth
2025	J	`jnl`	A Model Zoo on Phase Transitions in Neural Networks. CoRR Konstantin Schürholt, Léo Meynent, Yefan Zhou, Haiquan Lu, Yaoqing Yang, Damian Borth
2025	J	`jnl`	A Model Zoo on Phase Transitions in Neural Networks. J. Data-centric Mach. Learn. Res. Konstantin Schürholt, Léo Meynent, Yefan Zhou, Haiquan Lu, Yaoqing Yang, Damian Borth
2025	J	`jnl`	Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights. CoRR 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
2025	J	`jnl`	Learning Model Representations Using Publicly Available Model Hubs. CoRR Damian Falk, Konstantin Schürholt, Konstantinos Tzevelekakis, Léo Meynent, Damian Borth
2025	J	`jnl`	Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstruction. CoRR Léo Meynent, Ivan Melev, Konstantin Schürholt, Göran Kauermann, Damian Borth
2025	J	`jnl`	The Impact of Model Zoo Size and Composition on Weight Space Learning. CoRR Damian Falk, Konstantin Schürholt, Damian Borth
2024	J	`jnl`	Dirac-Bianconi Graph Neural Networks - Enabling Non-Diffusive Long-Range Graph Predictions. CoRR Christian Nauck, Rohan Gorantla, Michael Lindner, Konstantin Schürholt, Antonia S. J. S. Mey, Frank Hellmann
2024	—	`conf`	Dirac–Bianconi Graph Neural Networks – Enabling Non-Diffusive Long-Range Graph Predictions. GRaM Christian Nauck, Rohan Gorantla, Michael Lindner, Konstantin Schürholt, Antonia S. J. S. Mey, Frank Hellmann
2024	J	`jnl`	Hyper-Representations: Learning from Populations of Neural Networks. CoRR Konstantin Schürholt
2024	A*	`conf`	MD tree: a model-diagnostic tree grown on loss landscape. ICML Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang
2024	J	`jnl`	MD tree: a model-diagnostic tree grown on loss landscape. CoRR Yefan Zhou, Jianlong Chen, Qinxue Cao, Konstantin Schürholt, Yaoqing Yang
2024	A*	`conf`	Towards Scalable and Versatile Weight Space Learning. ICML Konstantin Schürholt, Michael W. Mahoney, Damian Borth
2024	J	`jnl`	Towards Scalable and Versatile Weight Space Learning. CoRR Konstantin Schürholt, Michael W. Mahoney, Damian Borth
2023	C	`conf`	Eurosat Model Zoo: A Dataset and Benchmark on Populations of Neural Networks and Its Sparsified Model Twins. IGARSS Dominik Honegger, Konstantin Schürholt, Linus Scheibenreif, Damian Borth
2023	J	`jnl`	Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models. CoRR Dominik Honegger, Konstantin Schürholt, Damian Borth
2022	J	`jnl`	Dynamic stability of power grids - new datasets for Graph Neural Networks. CoRR Christian Nauck, Michael Lindner, Konstantin Schürholt, Frank Hellmann
2022	A*	`conf`	Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. NeurIPS Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
2022	J	`jnl`	Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights. CoRR Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
2022	J	`jnl`	Hyper-Representations for Pre-Training and Transfer Learning. CoRR Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
2022	A*	`conf`	Model Zoos: A Dataset of Diverse Populations of Neural Network Models. NeurIPS Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
2022	J	`jnl`	Model Zoos: A Dataset of Diverse Populations of Neural Network Models. CoRR Konstantin Schürholt, Diyar Taskiran, Boris Knyazev, Xavier Giró-i-Nieto, Damian Borth
2022	J	`jnl`	Towards dynamic stability analysis of sustainable power grids using graph neural networks. CoRR Christian Nauck, Michael Lindner, Konstantin Schürholt, Frank Hellmann
2021	J	`jnl`	Predicting Dynamic Stability of Power Grids using Graph Neural Networks. CoRR Christian Nauck, Michael Lindner, Konstantin Schürholt, Haoming Zhang, Paul Schultz, Jürgen Kurths, Ingrid Isenhardt, Frank Hellmann
2021	A*	`conf`	Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction. NeurIPS Konstantin Schürholt, Dimche Kostadinov, Damian Borth
2021	J	`jnl`	Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction. CoRR Konstantin Schürholt, Dimche Kostadinov, Damian Borth
2020	J	`jnl`	An Investigation of the Weight Space for Version Control of Neural Networks. CoRR Konstantin Schürholt, Damian Borth