| Reliability of cka as a similarity measure in deep learning MR Davari, S Horoi, A Natik, G Lajoie, G Wolf, E Belilovsky arXiv preprint arXiv:2210.16156, 2022 | 20 | 2022 |
| On the inadequacy of CKA as a measure of similarity in deep learning MR Davari, S Horoi, A Natik, G Lajoie, G Wolf, E Belilovsky ICLR 2022 Workshop on Geometrical and Topological Representation Learning, 2022 | 12 | 2022 |
| Exploring the geometry and topology of neural network loss landscapes S Horoi, J Huang, B Rieck, G Lajoie, G Wolf, S Krishnaswamy International Symposium on Intelligent Data Analysis, 171-184, 2022 | 11 | 2022 |
| Low-dimensional dynamics of encoding and learning in recurrent neural networks S Horoi, V Geadah, G Wolf, G Lajoie Advances in Artificial Intelligence: 33rd Canadian Conference on Artificial …, 2020 | 6 | 2020 |
| Goal-driven optimization of single-neuron properties in artificial networks reveals regularization role of neural diversity and adaptation V Geadah, S Horoi, G Kerg, G Wolf, G Lajoie bioRxiv, 2022.04. 29.489963, 2022 | 4 | 2022 |
| Advantages of biologically-inspired adaptive neural activation in RNNs during learning V Geadah, G Kerg, S Horoi, G Wolf, G Lajoie arXiv preprint arXiv:2006.12253, 2020 | 3 | 2020 |
| Visualizing high-dimensional trajectories on the loss-landscape of ANNs S Horoi, J Huang, G Wolf, S Krishnaswamy | 2 | 2020 |
| Internal representation dynamics and geometry in recurrent neural networks S Horoi, G Lajoie, G Wolf arXiv preprint arXiv:2001.03255, 2020 | 2 | 2020 |
| Deceiving the CKA Similarity Measure in Deep Learning MR Davari, S Horoi, A Natik, G Lajoie, G Wolf, E Belilovsky NeurIPS ML Safety Workshop, 2022 | 1 | 2022 |
| CCA Merge: Merging Many Neural Networks with Canonical Correlation Analysis S Horoi, AMO Camacho, E Belilovsky, G Wolf | | |
| Harmony in Diversity: Merging Neural Networks with Canonical Correlation Analysis S Horoi, AMO Camacho, E Belilovsky, G Wolf ICLR 2024 Workshop on Representational Alignment, 0 | | |
