Ullrich, Karen

22 publications

ICML 2025 Aligned Multi Objective Optimization Yonathan Efroni, Ben Kretzu, Daniel R. Jiang, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich

ICCV 2025 DIMCIM: A Quantitative Evaluation Framework for Default-Mode Diversity and Generalization in Text-to-Image Generative Models Revant Teotia, Candace Ross, Karen Ullrich, Sumit Chopra, Adriana Romero-Soriano, Melissa Hall, Matthew Muckley

ICLR 2025 Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles Buu Phan, Brandon Amos, Itai Gat, Marton Havasi, Matthew J. Muckley, Karen Ullrich

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

NeurIPSW 2024 Aligned Multi-Objective Optimization Yonathan Efroni, Daniel Jiang, Ben Kretzu, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich

TMLR 2024 An Optimal Control Perspective on Diffusion-Based Generative Modeling Julius Berner, Lorenz Richter, Karen Ullrich

NeurIPS 2024 End-to-End Causal Effect Estimation from Unstructured Natural Language Data Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison

ICMLW 2024 End-to-End Causal Effect Estimation from Unstructured Natural Language Data Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul Krishnan, Chris J. Maddison

NeurIPS 2024 Mission Impossible: A Statistical Perspective on Jailbreaking LLMs Jingtong Su, Julia Kempe, Karen Ullrich

ICMLW 2024 Mission Impossible: A Statistical Perspective on Jailbreaking LLMs Jingtong Su, Julia Kempe, Karen Ullrich

ICMLW 2024 Understanding and Mitigating Tokenization Bias in Language Models Buu Phan, Marton Havasi, Matthew J. Muckley, Karen Ullrich

TMLR 2023 Image Compression with Product Quantized Masked Image Modeling Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Herve Jegou

ICML 2023 Improving Statistical Fidelity for Neural Image Compression with Implicit Local Likelihood Models Matthew J. Muckley, Alaaeldin El-Nouby, Karen Ullrich, Herve Jegou, Jakob Verbeek

NeurIPSW 2022 An Optimal Control Perspective on Diffusion-Based Generative Modeling Julius Berner, Lorenz Richter, Karen Ullrich

ICML 2021 Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding Yangjun Ruan, Karen Ullrich, Daniel S Severo, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris Maddison

ICLRW 2021 Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding Yangjun Ruan, Karen Ullrich, Daniel Severo, James Townsend, Ashish J Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison

NeurIPS 2021 Lossy Compression for Lossless Prediction Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J Maddison

ICLRW 2021 Lossy Compression for Lossless Prediction Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison

NeurIPSW 2021 Your Dataset Is a Multiset and You Should Compress It like One Daniel Severo, James Townsend, Ashish J Khisti, Alireza Makhzani, Karen Ullrich

UAI 2019 Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem Karen Ullrich, Rianne Berg, Marcus Brubaker, David Fleet, Max Welling

NeurIPS 2017 Bayesian Compression for Deep Learning Christos Louizos, Karen Ullrich, Max Welling

ICLR 2017 Soft Weight-Sharing for Neural Network Compression Karen Ullrich, Edward Meeds, Max Welling