Exploiting program-level masking and error propagation for constrained reliability optimization. - Muhammad Shafique 001; Semeen Rehman; Pau Vilimelis Aceituno; Jörg Henkel (DAC, 2013)

Leveraging variable function resilience for selective software reliability on unreliable hardware. - Semeen Rehman; Muhammad Shafique 001; Pau Vilimelis Aceituno; Florian Kriebel; Jian-Jia Chen; Jörg Henkel (DATE, 2013)

ACSEM: accuracy-configurable fast soft error masking analysis in combinatorial circuits. - Florian Kriebel; Semeen Rehman; Duo Sun; Pau Vilimelis Aceituno; Muhammad Shafique 001; Jörg Henkel (DATE, 2015)

Tailoring Artificial Neural Networks for Optimal Learning. - Pau Vilimelis Aceituno; Yan Gang; Yang-Yu Liu (CoRR, 2017)

Training Delays in Spiking Neural Networks. - Laura State; Pau Vilimelis Aceituno (ICANN (1), 2019)

Spiking time-dependent plasticity leads to efficient coding of predictions. - Pau Vilimelis Aceituno; Masud Ehsani; Jürgen Jost (Biol. Cybern., 2020)

Structure, Dynamics and Self-Organization in Recurrent Neural Networks: From Machine Learning to Theoretical Neuroscience. - Pau Vilimelis Aceituno (2020)

Eigenvalues of Random Signed Graphs with Cycles: A Graph-Centered View of the Method of Moments with Practical Applications. - Pau Vilimelis Aceituno (COMPLEX NETWORKS, 2021)

Credit Assignment in Neural Networks through Deep Feedback Control. - Alexander Meulemans; Matilde Tristany Farinha; Javier García Ordóñez; Pau Vilimelis Aceituno; João Sacramento; Benjamin F. Grewe (NeurIPS, 2021)

Minimizing costs of communication with random constant weight codes. - Pau Vilimelis Aceituno (CoRR, 2021)

Information Theory Limits of Neuromorphic Energy Efficiency. - Pau Vilimelis Aceituno (NICE, 2022)

Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel. - Seijin Kobayashi; Pau Vilimelis Aceituno; Johannes von Oswald (NeurIPS, 2022)

Learning cortical hierarchies with temporal Hebbian updates. - Pau Vilimelis Aceituno; Matilde Tristany Farinha; Reinhard Loidl; Benjamin F. Grewe (Frontiers Comput. Neurosci., 2023)

Bio-inspired, task-free continual learning through activity regularization. - Francesco Lässig; Pau Vilimelis Aceituno; Martino Sorbaro 001; Benjamin F. Grewe (Biol. Cybern., 2023)

The Role of Temporal Hierarchy in Spiking Neural Networks. - Filippo Moro; Pau Vilimelis Aceituno; Laura Kriener; Melika Payvand (CoRR, 2024)

The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training. - Matteo Saponati; Pascal Sager; Pau Vilimelis Aceituno; Thilo Stadelmann; Benjamin F. Grewe (CoRR, 2025)

Temporal horizons in forecasting: a performance-learnability trade-off. - Pau Vilimelis Aceituno; Jack William Miller; Noah Marti; Youssef Farag; Victor Boussange (CoRR, 2025)