Deep Neural Networks in a Mathematical Framework AL Caterini, DE Chang Springer International Publishing, 2018 | 220* | 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 | 127 | 2020 |
Hamiltonian variational auto-encoder AL Caterini, A Doucet, D Sejdinovic Advances in Neural Information Processing Systems 31, 2018 | 112 | 2018 |
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models G Stein, J Cresswell, R Hosseinzadeh, Y Sui, B Ross, V Villecroze, Z Liu, ... Advances in Neural Information Processing Systems 36, 2024 | 76 | 2024 |
Verifying the union of manifolds hypothesis for image data BCA Brown, AL Caterini, BL Ross, JC Cresswell, G Loaiza-Ganem arXiv preprint arXiv:2207.02862, 2022 | 55* | 2022 |
Rectangular flows for manifold learning AL Caterini, G Loaiza-Ganem, G Pleiss, JP Cunningham Advances in Neural Information Processing Systems 34, 30228-30241, 2021 | 44 | 2021 |
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 | 44 | 2015 |
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 | 37 | 2022 |
Diagnosing and fixing manifold overfitting in deep generative models G Loaiza-Ganem, BL Ross, JC Cresswell, AL Caterini arXiv preprint arXiv:2204.07172, 2022 | 24 | 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 | 21 | 2022 |
Variational inference with continuously-indexed normalizing flows A Caterini, R Cornish, D Sejdinovic, A Doucet Uncertainty in Artificial Intelligence, 44-53, 2021 | 20 | 2021 |
Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections G Loaiza-Ganem, BL Ross, R Hosseinzadeh, AL Caterini, JC Cresswell arXiv preprint arXiv:2404.02954, 2024 | 11 | 2024 |
A Novel Mathematical Framework for the Analysis of Neural Networks A Caterini University of Waterloo, 2017 | 11 | 2017 |
Neural Implicit Manifold Learning for Topology-Aware Density Estimation BL Ross, G Loaiza-Ganem, AL Caterini, JC Cresswell Transactions on Machine Learning Research, 2023 | 10* | 2023 |
TabPFGen--Tabular Data Generation with TabPFN J Ma, A Dankar, G Stein, G Yu, A Caterini arXiv preprint arXiv:2406.05216, 2024 | 9 | 2024 |
Denoising deep generative models G Loaiza-Ganem, BL Ross, L Wu, JP Cunningham, JC Cresswell, ... Proceedings on, 41-50, 2023 | 8 | 2023 |
A Geometric Explanation of the Likelihood OOD Detection Paradox H Kamkari, BL Ross, JC Cresswell, AL Caterini, RG Krishnan, ... arXiv preprint arXiv:2403.18910, 2024 | 7 | 2024 |
In-Context Data Distillation with TabPFN J Ma, V Thomas, G Yu, A Caterini arXiv preprint arXiv:2402.06971, 2024 | 7 | 2024 |
Calochallenge 2022: A community challenge for fast calorimeter simulation C Krause, MF Giannelli, G Kasieczka, B Nachman, D Salamani, D Shih, ... arXiv preprint arXiv:2410.21611, 2024 | 5 | 2024 |
Retrieval & Fine-Tuning for In-Context Tabular Models V Thomas, J Ma, R Hosseinzadeh, K Golestan, G Yu, M Volkovs, ... arXiv preprint arXiv:2406.05207, 2024 | 3 | 2024 |