| Deep Neural Networks in a Mathematical Framework AL Caterini, DE Chang Springer International Publishing, 2018 | 168* | 2018 |
| Relaxing bijectivity constraints with continuously indexed normalising flows R Cornish, A Caterini, G Deligiannidis, A Doucet International conference on machine learning, 2133-2143, 2020 | 99* | 2020 |
| Hamiltonian variational auto-encoder AL Caterini, A Doucet, D Sejdinovic Advances in Neural Information Processing Systems 31, 2018 | 93 | 2018 |
| Algorithmic acceleration of parallel ALS for collaborative filtering: Speeding up distributed big data recommendation in spark M Winlaw, MB Hynes, A Caterini, H De Sterck 2015 IEEE 21st International Conference on Parallel and Distributed Systems …, 2015 | 43 | 2015 |
| Rectangular flows for manifold learning AL Caterini, G Loaiza-Ganem, G Pleiss, JP Cunningham Advances in Neural Information Processing Systems 34, 30228-30241, 2021 | 32 | 2021 |
| Verifying the union of manifolds hypothesis for image data BCA Brown, AL Caterini, BL Ross, JC Cresswell, G Loaiza-Ganem The Eleventh International Conference on Learning Representations, 2022 | 15* | 2022 |
| Variational inference with continuously-indexed normalizing flows A Caterini, R Cornish, D Sejdinovic, A Doucet Uncertainty in Artificial Intelligence, 44-53, 2021 | 13 | 2021 |
| Diagnosing and fixing manifold overfitting in deep generative models G Loaiza-Ganem, BL Ross, JC Cresswell, AL Caterini arXiv preprint arXiv:2204.07172, 2022 | 11 | 2022 |
| CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds JC Cresswell, BL Ross, G Loaiza-Ganem, H Reyes-Gonzalez, M Letizia, ... arXiv preprint arXiv:2211.15380, 2022 | 10 | 2022 |
| Entropic issues in likelihood-based ood detection AL Caterini, G Loaiza-Ganem I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 21-26, 2022 | 7 | 2022 |
| A Novel Mathematical Framework for the Analysis of Neural Networks A Caterini University of Waterloo, 2017 | 7 | 2017 |
| Neural implicit manifold learning for topology-aware generative modelling BL Ross, G Loaiza-Ganem, AL Caterini, JC Cresswell arXiv preprint arXiv:2206.11267, 2022 | 5 | 2022 |
| Denoising Deep Generative Models G Loaiza-Ganem, BL Ross, L Wu, JP Cunningham, JC Cresswell, ... Proceedings on, 41-50, 2023 | 3 | 2023 |
| Detecting anthropogenic cloud perturbations with deep learning D Watson-Parris, S Sutherland, M Christensen, A Caterini, D Sejdinovic, ... | 2 | 2019 |
| Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models G Stein, JC Cresswell, R Hosseinzadeh, Y Sui, BL Ross, V Villecroze, ... arXiv preprint arXiv:2306.04675, 2023 | 1 | 2023 |
| Lossless compression using continuously-indexed normalizing flows A Golinski, AL Caterini Neural Compression: From Information Theory to Applications--Workshop@ ICLR 2021, 2021 | 1 | 2021 |
| C-learning: Horizon-aware cumulative accessibility estimation P Naderian, G Loaiza-Ganem, HJ Braviner, AL Caterini, JC Cresswell, ... arXiv preprint arXiv:2011.12363, 2020 | 1 | 2020 |
| TabPFGen–Tabular Data Generation with TabPFN J Ma, A Dankar, G Stein, G Yu, A Caterini NeurIPS 2023 Second Table Representation Learning Workshop, 2023 | | 2023 |
| Correcting manifold overfitting of probabilistic models GL Ganem, BL Ross, JC Cresswell, AL Caterini US Patent App. 18/083,345, 2023 | | 2023 |
| Relating Regularization and Generalization through the Intrinsic Dimension of Activations BCA Brown, J Juravsky, AL Caterini, G Loaiza-Ganem arXiv preprint arXiv:2211.13239, 2022 | | 2022 |
Gabriel Loaiza-GanemLayer 6 AIVerified email at layer6.ai
