Maximum Entropy Flow Networks. - Gabriel Loaiza-Ganem; Yuanjun Gao; John P. Cunningham (ICLR (Poster), 2017)

Deep Random Splines for Point Process Intensity Estimation. - Gabriel Loaiza-Ganem; John P. Cunningham (DGS@ICLR, 2019)

The continuous Bernoulli: fixing a pervasive error in variational autoencoders. - Gabriel Loaiza-Ganem; John P. Cunningham (NeurIPS, 2019)

Deep Random Splines for Point Process Intensity Estimation of Neural Population Data. - Gabriel Loaiza-Ganem; Sean Perkins; Karen Schroeder; Mark M. Churchland; John P. Cunningham (NeurIPS, 2019)

Advances in Deep Generative Modeling With Applications to Image Generation and Neuroscience. - Gabriel Loaiza-Ganem (2019)

Uses and Abuses of the Cross-Entropy Loss: Case Studies in Modern Deep Learning. - Elliott Gordon-Rodríguez; Gabriel Loaiza-Ganem; Geoff Pleiss; John P. Cunningham (ICBINB@NeurIPS, 2020)

The continuous categorical: a novel simplex-valued exponential family. - Elliott Gordon-Rodríguez; Gabriel Loaiza-Ganem; John P. Cunningham (ICML, 2020)

Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax. - Andres Potapczynski; Gabriel Loaiza-Ganem; John P. Cunningham (NeurIPS, 2020)

Entropic Issues in Likelihood-Based OOD Detection. - Anthony L. Caterini; Gabriel Loaiza-Ganem (ICBINB@NeurIPS, 2021)

C-Learning: Horizon-Aware Cumulative Accessibility Estimation. - Panteha Naderian; Gabriel Loaiza-Ganem; Harry J. Braviner; Anthony L. Caterini; Jesse C. Cresswell; Tong Li; Animesh Garg (ICLR, 2021)

Rectangular Flows for Manifold Learning. - Anthony L. Caterini; Gabriel Loaiza-Ganem; Geoff Pleiss; John P. Cunningham (NeurIPS, 2021)

Denoising Deep Generative Models. - Gabriel Loaiza-Ganem; Brendan Leigh Ross; Luhuan Wu; John P. Cunningham; Jesse C. Cresswell; Anthony L. Caterini (ICBINB, 2022)

Bayesian Nonparametrics for Offline Skill Discovery. - Valentin Villecroze; Harry J. Braviner; Panteha Naderian; Chris J. Maddison; Gabriel Loaiza-Ganem (ICML, 2022)

On the Normalizing Constant of the Continuous Categorical Distribution. - Elliott Gordon-Rodríguez; Gabriel Loaiza-Ganem; Andres Potapczynski; John P. Cunningham (CoRR, 2022)

Neural Implicit Manifold Learning for Topology-Aware Generative Modelling. - Brendan Leigh Ross; Gabriel Loaiza-Ganem; Anthony L. Caterini; Jesse C. Cresswell (CoRR, 2022)

The Union of Manifolds Hypothesis and its Implications for Deep Generative Modelling. - Bradley C. A. Brown; Anthony L. Caterini; Brendan Leigh Ross; Jesse C. Cresswell; Gabriel Loaiza-Ganem (CoRR, 2022)

Relating Regularization and Generalization through the Intrinsic Dimension of Activations. - Bradley C. A. Brown; Jordan Juravsky; Anthony L. Caterini; Gabriel Loaiza-Ganem (CoRR, 2022)

CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds. - Jesse C. Cresswell; Brendan Leigh Ross; Gabriel Loaiza-Ganem; Humberto Reyes-González; Marco Letizia; Anthony L. Caterini (CoRR, 2022)

Diagnosing and Fixing Manifold Overfitting in Deep Generative Models. - Gabriel Loaiza-Ganem; Brendan Leigh Ross; Jesse C. Cresswell; Anthony L. Caterini (Trans. Mach. Learn. Res., 2022)

Verifying the Union of Manifolds Hypothesis for Image Data. - Bradley C. A. Brown; Anthony L. Caterini; Brendan Leigh Ross; Jesse C. Cresswell; Gabriel Loaiza-Ganem (ICLR, 2023)

TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. - Zhaoyan Liu; Noël Vouitsis; Satya Krishna Gorti; Jimmy Ba; Gabriel Loaiza-Ganem (ICML, 2023)

Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models. - George Stein; Jesse C. Cresswell; Rasa Hosseinzadeh; Yi Sui 001; Brendan Leigh Ross; Valentin Villecroze; Zhaoyan Liu; Anthony L. Caterini; J. Eric T. Taylor; Gabriel Loaiza-Ganem (NeurIPS, 2023)

Data-Efficient Multimodal Fusion on a Single GPU. - Noël Vouitsis; Zhaoyan Liu; Satya Krishna Gorti; Valentin Villecroze; Jesse C. Cresswell; Guangwei Yu; Gabriel Loaiza-Ganem; Maksims Volkovs (CVPR, 2024)

A Geometric Explanation of the Likelihood OOD Detection Paradox. - Hamidreza Kamkari; Brendan Leigh Ross; Jesse C. Cresswell; Anthony L. Caterini; Rahul G. Krishnan; Gabriel Loaiza-Ganem (ICML, 2024)

A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models. - Hamidreza Kamkari; Brendan Leigh Ross; Rasa Hosseinzadeh; Jesse C. Cresswell; Gabriel Loaiza-Ganem (NeurIPS, 2024)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - 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; et al. (CoRR, 2024)

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples. - Noël Vouitsis; Rasa Hosseinzadeh; Brendan Leigh Ross; Valentin Villecroze; Satya Krishna Gorti; Jesse C. Cresswell; Gabriel Loaiza-Ganem (CoRR, 2024)

Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections. - Gabriel Loaiza-Ganem; Brendan Leigh Ross; Rasa Hosseinzadeh; Anthony L. Caterini; Jesse C. Cresswell (Trans. Mach. Learn. Res., 2024)

Neural Implicit Manifold Learning for Topology-Aware Density Estimation. - Brendan Leigh Ross; Gabriel Loaiza-Ganem; Anthony L. Caterini; Jesse C. Cresswell (Trans. Mach. Learn. Res., 2024)

A Geometric Framework for Understanding Memorization in Generative Models. - Brendan Leigh Ross; Hamidreza Kamkari; Tongzi Wu; Rasa Hosseinzadeh; Zhaoyan Liu; George Stein; Jesse C. Cresswell; Gabriel Loaiza-Ganem (ICLR, 2025)

Deep Ensembles Secretly Perform Empirical Bayes. - Gabriel Loaiza-Ganem; Valentin Villecroze; Yixin Wang (CoRR, 2025)

Last Layer Empirical Bayes. - Valentin Villecroze; Yixin Wang; Gabriel Loaiza-Ganem (CoRR, 2025)

Textual Bayes: Quantifying Uncertainty in LLM-Based Systems. - Brendan Leigh Ross; Noël Vouitsis; Atiyeh Ashari Ghomi; Rasa Hosseinzadeh; Ji Xin; Zhaoyan Liu; Yi Sui 001; Shiyi Hou; Kin Kwan Leung; Gabriel Loaiza-Ganem; Jesse C. Cresswell (CoRR, 2025)

On Convolutions, Intrinsic Dimension, and Diffusion Models. - Kin Kwan Leung; Rasa Hosseinzadeh; Gabriel Loaiza-Ganem (CoRR, 2025)