A Variational-Sequential Graph Autoencoder for Neural Architecture Performance Prediction. - David Friede; Jovita Lukasik; Heiner Stuckenschmidt; Margret Keuper (CoRR, 2019)

Neural Architecture Performance Prediction Using Graph Neural Networks. - Jovita Lukasik; David Friede; Heiner Stuckenschmidt; Margret Keuper (GCPR, 2020)

A Benders Decomposition Approach to Correlation Clustering. - Jovita Lukasik; Margret Keuper; Maneesh Singh 001; Julian Yarkony (MLHPC/AI4S@SC, 2020)

NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search. - Julien Siems; Lucas Zimmer; Arber Zela; Jovita Lukasik; Margret Keuper; Frank Hutter (CoRR, 2020)

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search. - Jovita Lukasik; David Friede; Arber Zela; Heiner Stuckenschmidt; Frank Hutter; Margret Keuper (CoRR, 2020)

Smooth Variational Graph Embeddings for Efficient Neural Architecture Search. - Jovita Lukasik; David Friede; Arber Zela; Frank Hutter; Margret Keuper (IJCNN, 2021)

DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity. - Jonas Geiping; Jovita Lukasik; Margret Keuper; Michael Moeller 001 (CoRR, 2021)

Learning Where to Look - Generative NAS is Surprisingly Efficient. - Jovita Lukasik; Steffen Jung 001; Margret Keuper (ECCV (23), 2022)

Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS Benchmarks. - Arber Zela; Julien Niklas Siems; Lucas Zimmer; Jovita Lukasik; Margret Keuper; Frank Hutter (ICLR, 2022)

Neural Architecture Design and Robustness: A Dataset. - Steffen Jung 001; Jovita Lukasik; Margret Keuper (ICLR, 2023)

An Evaluation of Zero-Cost Proxies - from Neural Architecture Performance to Model Robustness. - Jovita Lukasik; Michael Möller 001; Margret Keuper (CoRR, 2023)

Improving Native CNN Robustness with Filter Frequency Regularization. - Jovita Lukasik; Paul Gavrikov; Janis Keuper; Margret Keuper (Trans. Mach. Learn. Res., 2023)

Topology Learning for Prediction, Generation, and Robustness in Neural Architecture Search. - Jovita Lukasik (2023)

Surprisingly Strong Performance Prediction with Neural Graph Features. - Gabriela Kadlecová; Jovita Lukasik; Martin Pilát; Petra Vidnerová; Mahmoud Safari; Roman Neruda; Frank Hutter (ICML, 2024)

Implicit Representations for Constrained Image Segmentation. - Jan Philipp Schneider; Mishal Fatima; Jovita Lukasik; Andreas Kolb 001; Margret Keuper; Michael Moeller 001 (ICML, 2024)

Are Vision Language Models Texture or Shape Biased and Can We Steer Them? - Paul Gavrikov; Jovita Lukasik; Steffen Jung 001; Robert Geirhos; Bianca Lamm; Muhammad Jehanzeb Mirza; Margret Keuper; Janis Keuper (CoRR, 2024)

Can We Talk Models Into Seeing the World Differently? - Paul Gavrikov; Jovita Lukasik; Steffen Jung 001; Robert Geirhos; Muhammad Jehanzeb Mirza; Margret Keuper; Janis Keuper (ICLR, 2025)

Transferrable Surrogates in Expressive Neural Architecture Search Spaces. - Shiwen Qin; Gabriela Kadlecová; Martin Pilát; Shay B. Cohen; Roman Neruda; Elliot J. Crowley; Jovita Lukasik; Linus Ericsson (CoRR, 2025)

Smooth Model Compression without Fine-Tuning. - Christina Runkel; Natacha Kuete Meli; Jovita Lukasik; Ander Biguri; Carola-Bibiane Schönlieb; Michael Möller 001 (CoRR, 2025)

An Evaluation of Zero-Cost Proxies - from Neural Architecture Performance Prediction to Model Robustness. - Jovita Lukasik; Michael Möller 001; Margret Keuper (Int. J. Comput. Vis., 2025)