Michal Kucer

According to our database, Michal Kucer authored at least 16 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences.

Sweta Karlekar, Carolina Zheng, Magnus Saebo, Nicolas Beltran-Velez, Shuyang Yu, John Bowlan, Michal Kucer, David M. Blei

CoRR, February, 2026

2025

SPUS: A Lightweight and Parameter-Efficient Foundation Model for PDEs.

Abu Bucker Siddik, Diane Oyen, Alexander Most, Michal Kucer, Ayan Biswas

CoRR, October, 2025

LLM-Assisted Translation of Legacy FORTRAN Codes to C++: A Cross-Platform Study.

Nishath Rajiv Ranasinghe, Shawn M. Jones, Michal Kucer, Ayan Biswas, Daniel O'Malley, Alexander Most, Selma Liliane Wanna, Ajay Sreekumar

CoRR, April, 2025

The Trust Calibration Maturity Model for Characterizing and Communicating Trustworthiness of AI Systems.

Scott T. Steinmetz, Asmeret Naugle, Paul Schutte, Matthew Sweitzer, Alex Washburne, Lisa Linville, Daniel Krofcheck, Michal Kucer, Samuel Myren

CoRR, March, 2025

Posterior Mean Matching: Generative Modeling through Online Bayesian Inference.

Sebastian Salazar, Michal Kucer, Yixin Wang, Emily M. Casleton, David M. Blei

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

How Robust Are Energy-Based Models Trained With Equilibrium Propagation?

Siddharth Mansingh, Michal Kucer, Garrett T. Kenyon, Juston Moore, Michael A. Teti

CoRR, 2024

Energy-Based Models Trained with Equilibrium Propagation are Inherently Robust.

Siddharth Mansingh, Michal Kucer, Garrett T. Kenyon, Juston Moore, Michael A. Teti

Proceedings of the International Conference on Machine Learning and Applications, 2024

2023

DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding.

Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen

CoRR, 2023

2022

Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space.

Diane Oyen, Michal Kucer, Nick Hengartner, Har Simrat Singh

CoRR, 2022

DeepPatent: Large scale patent drawing recognition and retrieval.

Michal Kucer, Diane Oyen, Juan Castorena, Jian Wu

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Robustness to Label Noise Depends on the Shape of the Noise Distribution.

Diane Oyen, Michal Kucer, Nicolas W. Hengartner, Har Simrat Singh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

On visual self-supervision and its effect on model robustness.

Michal Kucer, Diane Oyen, Garrett T. Kenyon

CoRR, 2021

2019

A Detect-Then-Retrieve Model for Multi-Domain Fashion Item Retrieval.

Michal Kucer, Naila Murray

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Leveraging Expert Feature Knowledge for Predicting Image Aesthetics.

Michal Kucer, Alexander C. Loui, David W. Messinger

IEEE Trans. Image Process., 2018

Aesthetic Inference for Smart Mobile Devices.

Michal Kucer, David W. Messinger

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

2017

Augmenting Salient Foreground Detection using Fiedler Vector for Multi-Object Segmentation.

Michal Kucer, Nathan D. Cahill, Alexander C. Loui, David W. Messinger

Proceedings of the Computational Imaging XV, Burlingame, 2017