HesScale: Scalable Computation of Hessian Diagonals. - Mohamed Elsayed 003; A. Rupam Mahmood (CoRR, 2022)

Utility-based Perturbed Gradient Descent: An Optimizer for Continual Learning. - Mohamed Elsayed 003; A. Rupam Mahmood (CoRR, 2023)

Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning. - Mohamed Elsayed 003; A. Rupam Mahmood (ICLR, 2024)

Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning. - Mohamed Elsayed 003; Homayoon Farrahi; Felix Dangel; A. Rupam Mahmood (ICML, 2024)

Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. - Gautham Vasan; Mohamed Elsayed 003; Seyed Alireza Azimi; Jiamin He; Fahim Shahriar; Colin Bellinger; Martha White; Rupam Mahmood (NeurIPS, 2024)

Weight Clipping for Deep Continual and Reinforcement Learning. - Mohamed Elsayed 003; Qingfeng Lan; Clare Lyle; A. Rupam Mahmood (RLJ, 2024)

Streaming Deep Reinforcement Learning Finally Works. - Mohamed Elsayed 003; Gautham Vasan; A. Rupam Mahmood (CoRR, 2024)