Liebenwein, Lucas

6 publications

NeurIPS 2025 Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models Yonggan Fu, Xin Dong, Shizhe Diao, Matthijs Van keirsbilck, Hanrong Ye, Wonmin Byeon, Yashaswi Karnati, Lucas Liebenwein, Maksim Khadkevich, Alexander Keller, Jan Kautz, Yingyan Celine Lin, Pavlo Molchanov

NeurIPS 2021 Compressing Neural Networks: Towards Determining the Optimal Layer-Wise Decomposition Lucas Liebenwein, Alaa Maalouf, Dan Feldman, Daniela Rus

NeurIPS 2021 Sparse Flows: Pruning Continuous-Depth Models Lucas Liebenwein, Ramin Hasani, Alexander Amini, Daniela Rus

CoRL 2020 Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Lucas Liebenwein, Ryan Sander, Sertac Karaman, Daniela Rus

ICLR 2020 Provable Filter Pruning for Efficient Neural Networks Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus

ICLR 2019 Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus