Anthony L. Caterini

41 papers A* 8A 1B 1Journal 28Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Generalization Can Emerge in Tabular Foundation Models From a Single Table. CoRR Junwei Ma, Nour Shaheen, Alex Labach, Amine Mhedhbi, Frank Hutter, Anthony L. Caterini, Valentin Thomas
2024	A*	`conf`	A Geometric Explanation of the Likelihood OOD Detection Paradox. ICML Hamidreza Kamkari, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini, Rahul G. Krishnan, Gabriel Loaiza-Ganem
2024	J	`jnl`	A Geometric Explanation of the Likelihood OOD Detection Paradox. CoRR Hamidreza Kamkari, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini, Rahul G. Krishnan, Gabriel Loaiza-Ganem
2024	J	`jnl`	CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. CoRR Claudius Krause, Michele Faucci Giannelli, Gregor Kasieczka, Benjamin Nachman, Dalila Salamani, David Shih, Anna Zaborowska, Oz Amram, Kerstin Borras, Matthew R. Buckley, Erik Buhmann, Thorsten Buss, Renato Paulo Da Costa Cardoso, Anthony L. Caterini, Nadezda Chernyavskaya, Federico A. G. Corchia, Jesse C. Cresswell, Sascha Diefenbacher, Etienne Dreyer, Vijay Ekambaram, Engin Eren, Florian Ernst, Luigi Favaro, Matteo Franchini, Frank Gaede, Eilam Gross, Shih-Chieh Hsu, Kristina Jaruskova, Benno Käch, Jayant Kalagnanam, Raghav Kansal, Taewoo Kim, Dmitrii Kobylianskii, Anatolii Korol, William Korcari, Dirk Krücker, Katja Krüger, Marco Letizia, Shu Li, Qibin Liu, Xiulong Liu, Gabriel Loaiza-Ganem, Thandikire Madula, Peter McKeown, Isabell-A. Melzer-Pellmann, Vinicius Mikuni, Nam Nguyen, Ayodele Ore, Sofia Palacios Schweitzer, Ian Pang, Kevin Pedro, Tilman Plehn, Witold Pokorski, Huilin Qu, Piyush Raikwar, John A. Raine, Humberto Reyes-González, Lorenzo Rinaldi, Brendan Leigh Ross, Moritz A. W. Scham, Simon Schnake, Chase Shimmin, Eli Shlizerman, Nathalie Soybelman, Mudhakar Srivatsa, Kalliopi Tsolaki, Sofia Vallecorsa, Kyongmin Yeo, Rui Zhang
2024	J	`jnl`	Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections. CoRR Gabriel Loaiza-Ganem, Brendan Leigh Ross, Rasa Hosseinzadeh, Anthony L. Caterini, Jesse C. Cresswell
2024	J	`jnl`	Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections. Trans. Mach. Learn. Res. Gabriel Loaiza-Ganem, Brendan Leigh Ross, Rasa Hosseinzadeh, Anthony L. Caterini, Jesse C. Cresswell
2024	J	`jnl`	In-Context Data Distillation with TabPFN. CoRR Junwei Ma, Valentin Thomas, Guangwei Yu, Anthony L. Caterini
2024	J	`jnl`	Neural Implicit Manifold Learning for Topology-Aware Density Estimation. Trans. Mach. Learn. Res. Brendan Leigh Ross, Gabriel Loaiza-Ganem, Anthony L. Caterini, Jesse C. Cresswell
2024	A*	`conf`	Retrieval & Fine-Tuning for In-Context Tabular Models. NeurIPS Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini
2024	J	`jnl`	Retrieval & Fine-Tuning for In-Context Tabular Models. CoRR Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini
2024	J	`jnl`	TabDPT: Scaling Tabular Foundation Models. CoRR Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh, Hamidreza Kamkari, Alex Labach, Jesse C. Cresswell, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini
2024	J	`jnl`	TabPFGen - Tabular Data Generation with TabPFN. CoRR Junwei Ma, Apoorv Dankar, George Stein, Guangwei Yu, Anthony L. Caterini
2023	A*	`conf`	Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models. NeurIPS George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, J. Eric T. Taylor, Gabriel Loaiza-Ganem
2023	J	`jnl`	Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models. CoRR George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, J. Eric T. Taylor, Gabriel Loaiza-Ganem
2023	A*	`conf`	Verifying the Union of Manifolds Hypothesis for Image Data. ICLR Bradley C. A. Brown, Anthony L. Caterini, Brendan Leigh Ross, Jesse C. Cresswell, Gabriel Loaiza-Ganem
2022	J	`jnl`	CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds. CoRR Jesse C. Cresswell, Brendan Leigh Ross, Gabriel Loaiza-Ganem, Humberto Reyes-González, Marco Letizia, Anthony L. Caterini
2022	—	`conf`	Denoising Deep Generative Models. ICBINB Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini
2022	J	`jnl`	Denoising Deep Generative Models. CoRR Gabriel Loaiza-Ganem, Brendan Leigh Ross, Luhuan Wu, John P. Cunningham, Jesse C. Cresswell, Anthony L. Caterini
2022	J	`jnl`	Diagnosing and Fixing Manifold Overfitting in Deep Generative Models. CoRR Gabriel Loaiza-Ganem, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini
2022	J	`jnl`	Diagnosing and Fixing Manifold Overfitting in Deep Generative Models. Trans. Mach. Learn. Res. Gabriel Loaiza-Ganem, Brendan Leigh Ross, Jesse C. Cresswell, Anthony L. Caterini
2022	J	`jnl`	Neural Implicit Manifold Learning for Topology-Aware Generative Modelling. CoRR Brendan Leigh Ross, Gabriel Loaiza-Ganem, Anthony L. Caterini, Jesse C. Cresswell
2022	J	`jnl`	Relating Regularization and Generalization through the Intrinsic Dimension of Activations. CoRR Bradley C. A. Brown, Jordan Juravsky, Anthony L. Caterini, Gabriel Loaiza-Ganem
2022	J	`jnl`	The Union of Manifolds Hypothesis and its Implications for Deep Generative Modelling. CoRR Bradley C. A. Brown, Anthony L. Caterini, Brendan Leigh Ross, Jesse C. Cresswell, Gabriel Loaiza-Ganem
2021	A*	`conf`	C-Learning: Horizon-Aware Cumulative Accessibility Estimation. ICLR Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg
2021	—	`conf`	Entropic Issues in Likelihood-Based OOD Detection. ICBINB@NeurIPS Anthony L. Caterini, Gabriel Loaiza-Ganem
2021	J	`jnl`	Entropic Issues in Likelihood-Based OOD Detection. CoRR Anthony L. Caterini, Gabriel Loaiza-Ganem
2021	A*	`conf`	Rectangular Flows for Manifold Learning. NeurIPS Anthony L. Caterini, Gabriel Loaiza-Ganem, Geoff Pleiss, John P. Cunningham
2021	J	`jnl`	Rectangular Flows for Manifold Learning. CoRR Anthony L. Caterini, Gabriel Loaiza-Ganem, Geoff Pleiss, John P. Cunningham
2021	A	`conf`	Variational inference with continuously-indexed normalizing flows. UAI Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet
2020	J	`jnl`	C-Learning: Horizon-Aware Cumulative Accessibility Estimation. CoRR Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg
2020	A*	`conf`	Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows. ICML Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet
2020	J	`jnl`	Variational Inference with Continuously-Indexed Normalizing Flows. CoRR Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet
2019	J	`jnl`	Detecting anthropogenic cloud perturbations with deep learning. CoRR Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony L. Caterini, Dino Sejdinovic, Philip Stier
2019	J	`jnl`	Localised Generative Flows. CoRR Robert Cornish, Anthony L. Caterini, George Deligiannidis, Arnaud Doucet
2018	—	`book`	Deep Neural Networks in a Mathematical Framework Anthony L. Caterini, Dong Eui Chang
2018	A*	`conf`	Hamiltonian Variational Auto-Encoder. NeurIPS Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic
2018	J	`jnl`	Hamiltonian Variational Auto-Encoder. CoRR Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic
2016	J	`jnl`	A Geometric Framework for Convolutional Neural Networks. CoRR Anthony L. Caterini, Dong Eui Chang
2016	J	`jnl`	A Novel Representation of Neural Networks. CoRR Anthony L. Caterini, Dong Eui Chang
2015	B	`conf`	Algorithmic Acceleration of Parallel ALS for Collaborative Filtering: Speeding up Distributed Big Data Recommendation in Spark. ICPADS Manda Winlaw, Michael B. Hynes, Anthony L. Caterini, Hans De Sterck
2015	J	`jnl`	Algorithmic Acceleration of Parallel ALS for Collaborative Filtering: Speeding up Distributed Big Data Recommendation in Spark. CoRR Manda Winlaw, Michael B. Hynes, Anthony L. Caterini, Hans De Sterck