Evci, Utku

16 publications

CPAL 2025 Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna

NeurIPS 2025 Spark Transformer: Reactivating Sparsity in Transformer FFN and Attention Chong You, Kan Wu, Zhipeng Jia, Lin Chen, Srinadh Bhojanapalli, Jiaxian Guo, Utku Evci, Jan Wassenberg, Praneeth Netrapalli, Jeremiah J. Willcock, Suvinay Subramanian, Felix Chern, Alek Andreev, Shreya Pathak, Felix X. Yu, Prateek Jain, David E Culler, Henry Levy, Sanjiv Kumar

ICLR 2025 The Journey Matters: Average Parameter Count over Pre-Training Unifies Sparse and Dense Scaling Laws Tian Jin, Ahmed Imtiaz Humayun, Utku Evci, Suvinay Subramanian, Amir Yazdanbakhsh, Dan Alistarh, Gintare Karolina Dziugaite

ICLR 2024 Dynamic Sparse Training with Structured Sparsity Mike Lasby, Anna Golubeva, Utku Evci, Mihai Nica, Yani Ioannou

CPAL 2024 Jaxpruner: A Concise Library for Sparsity Research Joo Hyung Lee, Wonpyo Park, Nicole Elyse Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J.C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci

ICLR 2024 Scaling Laws for Sparsely-Connected Foundation Models Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby, Dan Alistarh, Utku Evci

ICML 2023 Scaling Vision Transformers to 22 Billion Parameters Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd Van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby

ICML 2023 The Dormant Neuron Phenomenon in Deep Reinforcement Learning Ghada Sokar, Rishabh Agarwal, Pablo Samuel Castro, Utku Evci

ICLR 2022 GradMax: Growing Neural Networks Using Gradient Information Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov

AAAI 2022 Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win Utku Evci, Yani Ioannou, Cem Keskin, Yann N. Dauphin

ICML 2022 Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C Mozer

ICML 2022 The State of Sparse Training in Deep Reinforcement Learning Laura Graesser, Utku Evci, Erich Elsen, Pablo Samuel Castro

ICLR 2021 Practical Real Time Recurrent Learning with a Sparse Approximation Jacob Menick, Erich Elsen, Utku Evci, Simon Osindero, Karen Simonyan, Alex Graves

ICLR 2020 Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Utku Evci, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle

ICML 2020 Rigging the Lottery: Making All Tickets Winners Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen

ICMLW 2019 The Difficulty of Training Sparse Neural Networks Utku Evci, Fabian Pedregosa, Aidan Gomez, Erich Elsen