One Step from the Locomotion to the Stepping Pattern. - Ronan Boulic; Utku Evci; Eray Molla; Phanindra Pisupati (CASA, 2016)

Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. - Levent Sagun; Utku Evci; V. Ugur Güney; Yann N. Dauphin; Léon Bottou (ICLR (Workshop), 2018)

Detecting Dead Weights and Units in Neural Networks. - Utku Evci (CoRR, 2018)

The Difficulty of Training Sparse Neural Networks. - Utku Evci; Fabian Pedregosa; Aidan N. Gomez; Erich Elsen (CoRR, 2019)

Natural Language Understanding with the Quora Question Pairs Dataset. - Lakshay Sharma; Laura Graesser; Nikita Nangia; Utku Evci (CoRR, 2019)

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 (ICLR, 2020)

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

A Practical Sparse Approximation for Real Time Recurrent Learning. - Jacob Menick; Erich Elsen; Utku Evci; Simon Osindero; Karen Simonyan; Alex Graves (CoRR, 2020)

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

A Unified Few-Shot Classification Benchmark to Compare Transfer and Meta Learning Approaches. - Vincent Dumoulin; Neil Houlsby; Utku Evci; Xiaohua Zhai; Ross Goroshin; Sylvain Gelly; Hugo Larochelle (NeurIPS Datasets and Benchmarks, 2021)

Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark. - Vincent Dumoulin; Neil Houlsby; Utku Evci; Xiaohua Zhai; Ross Goroshin; Sylvain Gelly; Hugo Larochelle (CoRR, 2021)

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

GradMax: Growing Neural Networks using Gradient Information. - Utku Evci; Bart van Merrienboer; Thomas Unterthiner; Fabian Pedregosa; Max Vladymyrov (ICLR, 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 (ICML, 2022)

Training Recipe for N: M Structured Sparsity with Decaying Pruning Mask. - Sheng-Chun Kao; Amir Yazdanbakhsh; Suvinay Subramanian; Shivani Agrawal; Utku Evci; Tushar Krishna (CoRR, 2022)

Scaling Vision Transformers to 22 Billion Parameters. - Mostafa Dehghani 001; Josip Djolonga; Basil Mustafa; Piotr Padlewski; Jonathan Heek; Justin Gilmer; Andreas Peter Steiner; Mathilde Caron; Robert Geirhos; Ibrahim Alabdulmohsin; Rodolphe Jenatton; Lucas Beyer; et al. (ICML, 2023)

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

JaxPruner: A concise library for sparsity research. - Joo Hyung Lee; Wonpyo Park; Nicole Mitchell; Jonathan Pilault; Johan S. Obando-Ceron; Han-Byul Kim; Namhoon Lee; Elias Frantar; Yun Long; Amir Yazdanbakhsh; Shivani Agrawal; Suvinay Subramanian; et al. (CoRR, 2023)

Jaxpruner: A Concise Library for Sparsity Research. - Joo Hyung Lee; Wonpyo Park; Nicole Mitchell; Jonathan Pilault; Johan Samir Obando Ceron; Han-Byul Kim; Namhoon Lee; Elias Frantar; Yun Long; Amir Yazdanbakhsh; Woohyun Han; Shivani Agrawal; et al. (CPAL, 2024)

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

Dynamic Sparse Training with Structured Sparsity. - Mike Lasby; Anna Golubeva; Utku Evci; Mihai Nica; Yani Ioannou (ICLR, 2024)

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 (CoRR, 2024)

Towards Optimal Adapter Placement for Efficient Transfer Learning. - Aleksandra Irena Nowak; Otniel-Bogdan Mercea; Anurag Arnab; Jonas Pfeiffer; Yann N. Dauphin; Utku Evci (CoRR, 2024)

Learning Parameter Sharing with Tensor Decompositions and Sparsity. - Cem Üyük; Mike Lasby; Mohamed Yassin; Utku Evci; Yani Ioannou (CoRR, 2024)

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 (CPAL, 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, 2025)

Compression Scaling Laws:Unifying Sparsity and Quantization. - Elias Frantar; Utku Evci; Wonpyo Park; Neil Houlsby; Dan Alistarh (CoRR, 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)

Spark Transformer: Reactivating Sparsity in 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; et al. (CoRR, 2025)