Garipov, Timur

9 publications

ICML 2025 Generative Data Mining with Longtail-Guided Diffusion David S Hayden, Mao Ye, Timur Garipov, Gregory P. Meyer, Carl Vondrick, Zhao Chen, Yuning Chai, Eric M Wolff, Siddhartha Srinivasa

ICMLW 2024 Diffusion Domain Expansion: Learning to Coordinate Pre-Trained Diffusion Models Egor Lifar, Semyon Savkin, Timur Garipov, Shangyuan Tong, Tommi Jaakkola

NeurIPS 2023 Compositional Sculpting of Iterative Generative Processes Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi Jaakkola

ICLR 2022 Adversarial Support Alignment Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola

ICLR 2020 Towards Understanding the True Loss Surface of Deep Neural Networks Using Random Matrix Theory and Iterative Spectral Methods Diego Granziol, Timur Garipov, Dmitry Vetrov, Stefan Zohren, Stephen Roberts, Andrew Gordon Wilson

NeurIPS 2019 A Simple Baseline for Bayesian Uncertainty in Deep Learning Wesley J Maddox, Pavel Izmailov, Timur Garipov, Dmitry P Vetrov, Andrew Gordon Wilson

UAI 2019 Subspace Inference for Bayesian Deep Learning Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko, Timur Garipov, Dmitry Vetrov, Andrew Gordon Wilson

UAI 2018 Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson

NeurIPS 2018 Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P Vetrov, Andrew G Wilson