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Pau Vilimelis Aceituno
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2020 – today
- 2024
- [i6]Filippo Moro, Pau Vilimelis Aceituno, Laura Kriener, Melika Payvand:
The Role of Temporal Hierarchy in Spiking Neural Networks. CoRR abs/2407.18838 (2024) - 2023
- [j3]Francesco Lässig, Pau Vilimelis Aceituno, Martino Sorbaro, Benjamin F. Grewe:
Bio-inspired, task-free continual learning through activity regularization. Biol. Cybern. 117(4): 345-361 (2023) - [j2]Pau Vilimelis Aceituno, Matilde Tristany Farinha, Reinhard Loidl, Benjamin F. Grewe:
Learning cortical hierarchies with temporal Hebbian updates. Frontiers Comput. Neurosci. 17 (2023) - 2022
- [c8]Pau Vilimelis Aceituno:
Information Theory Limits of Neuromorphic Energy Efficiency. NICE 2022: 86-87 - [c7]Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald:
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel. NeurIPS 2022 - [i5]Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald:
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel. CoRR abs/2210.09818 (2022) - [i4]Francesco Lässig, Pau Vilimelis Aceituno, Martino Sorbaro, Benjamin F. Grewe:
Bio-Inspired, Task-Free Continual Learning through Activity Regularization. CoRR abs/2212.04316 (2022) - 2021
- [c6]Pau Vilimelis Aceituno:
Eigenvalues of Random Signed Graphs with Cycles: A Graph-Centered View of the Method of Moments with Practical Applications. COMPLEX NETWORKS 2021: 390-400 - [c5]Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe:
Credit Assignment in Neural Networks through Deep Feedback Control. NeurIPS 2021: 4674-4687 - [i3]Pau Vilimelis Aceituno:
Minimizing costs of communication with random constant weight codes. CoRR abs/2105.02504 (2021) - [i2]Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe:
Credit Assignment in Neural Networks through Deep Feedback Control. CoRR abs/2106.07887 (2021) - 2020
- [b1]Pau Vilimelis Aceituno:
Structure, Dynamics and Self-Organization in Recurrent Neural Networks: From Machine Learning to Theoretical Neuroscience. Leipzig University, Germany, 2020 - [j1]Pau Vilimelis Aceituno, Masud Ehsani, Jürgen Jost:
Spiking time-dependent plasticity leads to efficient coding of predictions. Biol. Cybern. 114(1): 43-61 (2020)
2010 – 2019
- 2019
- [c4]Laura State, Pau Vilimelis Aceituno:
Training Delays in Spiking Neural Networks. ICANN (1) 2019: 713-717 - 2017
- [i1]Pau Vilimelis Aceituno, Yan Gang, Yang-Yu Liu:
Tailoring Artificial Neural Networks for Optimal Learning. CoRR abs/1707.02469 (2017) - 2015
- [c3]Florian Kriebel, Semeen Rehman, Duo Sun, Pau Vilimelis Aceituno, Muhammad Shafique, Jörg Henkel:
ACSEM: accuracy-configurable fast soft error masking analysis in combinatorial circuits. DATE 2015: 824-829 - 2013
- [c2]Muhammad Shafique, Semeen Rehman, Pau Vilimelis Aceituno, Jörg Henkel:
Exploiting program-level masking and error propagation for constrained reliability optimization. DAC 2013: 17:1-17:9 - [c1]Semeen Rehman, Muhammad Shafique, Pau Vilimelis Aceituno, Florian Kriebel, Jian-Jia Chen, Jörg Henkel:
Leveraging variable function resilience for selective software reliability on unreliable hardware. DATE 2013: 1759-1764
Coauthor Index
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last updated on 2024-08-25 19:11 CEST by the dblp team
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