| Hyperbolic Neural Networks OE Ganea*, G Bécigneul*, T Hofmann Accepted at NIPS 2018: Neural Information Processing Systems, 2018 | 243 | 2018 |
| Hyperbolic Entailment Cones for Learning Hierarchical Embeddings OE Ganea, G Bécigneul, T Hofmann Accepted at ICML 2018: International Conference on Machine Learning, 2018 | 153 | 2018 |
| Poincaré GloVe: Hyperbolic Word Embeddings A Tifrea*, G Bécigneul*, OE Ganea* Accepted at ICLR 2019: International Conference on Learning Representations, 2018 | 151 | 2018 |
| Riemannian Adaptive Optimization Methods G Bécigneul, OE Ganea Accepted at ICLR 2019: International Conference on Learning Representations, 2018 | 109 | 2018 |
| Constant Curvature Graph Convolutional Networks G Bachmann*, G Bécigneul*, OE Ganea Accepted at ICML 2020: International Conference on Machine Learning, 2019 | 37 | 2019 |
| Mixed-curvature variational autoencoders O Skopek, OE Ganea, G Bécigneul | 30 | 2020 |
| A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization F Alimisis, A Orvieto, G Bécigneul, A Lucchi Accepted at AISTATS 2020: Artificial Intelligence and Statistics, 2019 | 18 | 2019 |
| Mixed-curvature Variational Autoencoders O Skopek, OE Ganea, G Bécigneul Accepted at ICLR 2020: International Conference on Learning Representations, 2019 | 14 | 2019 |
| Optimal transport graph neural networks B Chen, G Bécigneul, OE Ganea, R Barzilay, T Jaakkola arXiv preprint arXiv:2006.04804, 2020 | 13 | 2020 |
| Computationally Tractable Riemannian Manifolds for Graph Embeddings C Cruceru, G Bécigneul, OE Ganea Accepted at AAAI 2021: Association for the Advancement of Artificial …, 2020 | 13 | 2020 |
| Momentum improves optimization on Riemannian manifolds F Alimisis, A Orvieto, G Becigneul, A Lucchi International Conference on Artificial Intelligence and Statistics, 1351-1359, 2021 | 9 | 2021 |
| Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities OE Ganea, S Gelly, G Bécigneul, A Severyn Accepted at ICML 2019: International Conference on Machine Learning, 2019 | 9 | 2019 |
| Practical Accelerated Optimization on Riemannian Manifolds F Alimisis, A Orvieto, G Bécigneul, A Lucchi Accepted at AISTATS 2021: Artificial Intelligence and Statistics, 2020 | 8 | 2020 |
| Bloom origami assays: practical group testing L Abraham, G Becigneul, B Coleman, B Scholkopf, A Shrivastava, ... arXiv preprint arXiv:2008.02641, 2020 | 3 | 2020 |
| On the effect of pooling on the geometry of representations G Bécigneul https://arxiv.org/pdf/1703.06726.pdf, 2017 | 3 | 2017 |
| Crackovid: Optimizing Group Testing L Abraham, G Bécigneul, B Schölkopf https://arxiv.org/pdf/2005.06413.pdf, 2020 | 2 | 2020 |
| Environment and Speaker Related Emotion Recognition in Conversations Z Zhong, S Yang, G Becigneul The 2nd International Conference on Computing and Data Science, 1-6, 2021 | 1 | 2021 |
| Escaping Flat Areas via Function-Preserving Structural Network Modifications Y Kilcher*, G Bécigneul*, T Hofmann https://openreview.net/pdf?id=H1eadi0cFQ, 2018 | 1 | 2018 |
| Riemannian Adaptive Optimization Methods OE Ganea, G Bécigneul 7th International Conference on Learning Representations (ICLR 2019), 2018 | 1 | 2018 |
| Parametrizing filters of a CNN with a GAN Y Kilcher*, G Bécigneul*, T Hofmann https://arxiv.org/pdf/1710.11386.pdf, 2017 | 1 | 2017 |
Octavian GaneaMIT, CSAILVerified email at csail.mit.edu
