Topological Insights into Sparse Neural Networks. - Shiwei Liu 003; Tim van der Lee; Anil Yaman; Zahra Atashgahi; Davide Ferraro; Ghada Sokar; Mykola Pechenizkiy; Decebal Constantin Mocanu (ECML/PKDD (3), 2020)

Topological Insights in Sparse Neural Networks. - Shiwei Liu 003; Tim van der Lee; Anil Yaman; Zahra Atashgahi; Davide Ferraro; Ghada Sokar; Mykola Pechenizkiy; Decebal Constantin Mocanu (CoRR, 2020)

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration. - Shiwei Liu 003; Tianlong Chen 001; Xiaohan Chen; Zahra Atashgahi; Lu Yin 006; Huanyu Kou; Li Shen 008; Mykola Pechenizkiy; Zhangyang Wang; Decebal Constantin Mocanu (NeurIPS, 2021)

FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity. - Shiwei Liu 003; Tianlong Chen 001; Zahra Atashgahi; Xiaohan Chen; Ghada Sokar; Elena Mocanu; Mykola Pechenizkiy; Zhangyang Wang; Decebal Constantin Mocanu (CoRR, 2021)

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity. - Shiwei Liu 003; Tianlong Chen 001; Zahra Atashgahi; Xiaohan Chen; Ghada Sokar; Elena Mocanu; Mykola Pechenizkiy; Zhangyang Wang; Decebal Constantin Mocanu (ICLR, 2022)

Where to Pay Attention in Sparse Training for Feature Selection? - Ghada Sokar; Zahra Atashgahi; Mykola Pechenizkiy; Decebal Constantin Mocanu (NeurIPS, 2022)

Memory-free Online Change-point Detection: A Novel Neural Network Approach. - Zahra Atashgahi; Decebal Constantin Mocanu; Raymond N. J. Veldhuis; Mykola Pechenizkiy (CoRR, 2022)

A brain-inspired algorithm for training highly sparse neural networks. - Zahra Atashgahi; Joost Pieterse; Shiwei Liu 003; Decebal Constantin Mocanu; Raymond N. J. Veldhuis; Mykola Pechenizkiy (Mach. Learn., 2022)

Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders. - Zahra Atashgahi; Ghada Sokar; Tim van der Lee; Elena Mocanu; Decebal Constantin Mocanu; Raymond N. J. Veldhuis; Mykola Pechenizkiy (Mach. Learn., 2022)

Cost-effective Artificial Neural Networks. - Zahra Atashgahi (IJCAI, 2023)

Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks. - Zahra Atashgahi; Xuhao Zhang; Neil Kichler; Shiwei Liu 003; Lu Yin 006; Mykola Pechenizkiy; Raymond N. J. Veldhuis; Decebal Constantin Mocanu (Trans. Mach. Learn. Res., 2023)

Supervised Feature Selection via Ensemble Gradient Information from Sparse Neural Networks. - Kaiting Liu; Zahra Atashgahi; Ghada Sokar; Mykola Pechenizkiy; Decebal Constantin Mocanu (AISTATS, 2024)

Unveiling the Power of Sparse Neural Networks for Feature Selection. - Zahra Atashgahi; Tennison Liu; Mykola Pechenizkiy; Raymond N. J. Veldhuis; Decebal Constantin Mocanu; Mihaela van der Schaar (ECAI, 2024)

Adaptive Sparsity Level During Training for Efficient Time Series Forecasting with Transformers. - Zahra Atashgahi; Mykola Pechenizkiy; Raymond N. J. Veldhuis; Decebal Constantin Mocanu (ECML/PKDD (1), 2024)

NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling. - Bram Grooten; Farid Hasanov; Chenxiang Zhang; Qiao Xiao; Boqian Wu; Zahra Atashgahi; Ghada Sokar; Shiwei Liu 003; Lu Yin 006; Elena Mocanu; Mykola Pechenizkiy; Decebal Constantin Mocanu (CoRR, 2025)