IP Session on Machine Learning Applications in IC Test-Related Tasks. - Ghada Sokar; Yassin Zakaria; Asmaa Rabie; Kareem Madkour; Ira Leventhal; Jochen Rivoir; Xinli Gu; Haralampos-G. D. Stratigopoulos (VTS, 2019)

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)

Self-Attention Meta-Learner for Continual Learning. - Ghada Sokar; Decebal Constantin Mocanu; Mykola Pechenizkiy (AAMAS, 2021)

Continual Lifelong Learning for Intelligent Agents. - Ghada Sokar (IJCAI, 2021)

Learning Invariant Representation for Continual Learning. - Ghada Sokar; Decebal Constantin Mocanu; Mykola Pechenizkiy (CoRR, 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)

Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning. - Ghada Sokar; Decebal Constantin Mocanu; Mykola Pechenizkiy (CoRR, 2021)

SpaceNet: Make Free Space for Continual Learning. - Ghada Sokar; Decebal Constantin Mocanu; Mykola Pechenizkiy (Neurocomputing, 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)

Dynamic Sparse Training for Deep Reinforcement Learning. - Ghada Sokar; Elena Mocanu; Decebal Constantin Mocanu; Mykola Pechenizkiy; Peter Stone 001 (IJCAI, 2022)

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

Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks. - Ghada Sokar; Decebal Constantin Mocanu; Mykola Pechenizkiy (ECML/PKDD (3), 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)

Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. - Bram Grooten; Ghada Sokar; Shibhansh Dohare; Elena Mocanu; Matthew E. Taylor; Mykola Pechenizkiy; Decebal Constantin Mocanu (AAMAS, 2023)

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

Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates. - Murat Onur Yildirim; Elif Ceren Gok Yildirim; Ghada Sokar; Decebal Constantin Mocanu; Joaquin Vanschoren (CPAL, 2024)

Mixtures of Experts Unlock Parameter Scaling for Deep RL. - Johan S. Obando-Ceron; Ghada Sokar; Timon Willi; Clare Lyle; Jesse Farebrother; Jakob Nicolaus Foerster; Gintare Karolina Dziugaite; Doina Precup; Pablo Samuel Castro (ICML, 2024)

Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL. - Ghada Sokar; Johan S. Obando-Ceron; Aaron C. Courville; Hugo Larochelle; Pablo Samuel Castro (ICLR, 2025)

Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning. - Ghada Sokar; Pablo Samuel Castro (CoRR, 2025)

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)

Continual Learning in Vision-Language Models via Aligned Model Merging. - Ghada Sokar; Gintare Karolina Dziugaite; Anurag Arnab; Ahmet Iscen; Pablo Samuel Castro; Cordelia Schmid (CoRR, 2025)

What Can Grokking Teach Us About Learning Under Nonstationarity? - Clare Lyle; Ghada Sokar; Razvan Pascanu; András György 001 (CoRR, 2025)