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Amir Joudaki
Amir Joudaki
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Cited by
Year
EEG-based functional brain networks: does the network size matter?
A Joudaki, N Salehi, M Jalili, MG Knyazeva
PloS one 7 (4), e35673, 2012
742012
Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures
E Barzegaran, A Joudaki, M Jalili, AO Rossetti, RS Frackowiak, ...
Frontiers in human neuroscience 6, 335, 2012
622012
Nonlinear Dimensionality Reduction via Path-Based Isometric Mapping
A Najafi, A Joudaki, E Fatemizadeh
IEEE, 2015
372015
Batch normalization orthogonalizes representations in deep random networks
H Daneshmand, A Joudaki, F Bach
Advances in Neural Information Processing Systems 34, 4896-4906, 2021
282021
Sparse binary relation representations for genome graph annotation
M Karasikov, H Mustafa, A Joudaki, S Javadzadeh-No, G Rätsch, ...
International Conference on Research in Computational Molecular Biology, 120-135, 2019
192019
Fast alignment-free similarity estimation by tensor sketching
A Joudaki, G Rätsch, A Kahles
bioRxiv, 2020.11. 13.381814, 2020
72020
Aligning distant sequences to graphs using long seed sketches
A Joudaki, A Meterez, H Mustafa, RG Koerkamp, A Kahles, G Rätsch
Genome Research 33 (7), 1208-1217, 2023
52023
On the impact of activation and normalization in obtaining isometric embeddings at initialization
A Joudaki, H Daneshmand, F Bach
Advances in Neural Information Processing Systems 36, 2024
42024
On bridging the gap between mean field and finite width deep random multilayer perceptron with batch normalization
A Joudaki, H Daneshmand, F Bach
International Conference on Machine Learning, 15388-15400, 2023
22023
Towards training without depth limits: Batch normalization without gradient explosion
A Meterez, A Joudaki, F Orabona, A Immer, G Rätsch, H Daneshmand
arXiv preprint arXiv:2310.02012, 2023
12023
Learning Genomic Sequence Representations using Graph Neural Networks over De Bruijn Graphs
K Kapuśniak, M Burger, G Rätsch, A Joudaki
arXiv preprint arXiv:2312.03865, 2023
2023
PCA Subspaces Are Not Always Optimal for Bayesian Learning
A Bense, A Joudaki, TGJ Rudner, V Fortuin
NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021
2021
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