Russell Tsuchida

Debarghya Ghoshdastidar

CoRR, February, 2025

Label Distribution Learning using the Squared Neural Family on the Probability Simplex.

[BibT_eX]

[DOI]

Daokun Zhang

Dino Sejdinovic

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems.

[BibT_eX]

[DOI]

Daniel MacKinlay

Daniel Edward Pagendam

Petra Kuhnert

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Open Set Label Shift with Test Time Out-of-Distribution Reference.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems.

[BibT_eX]

[DOI]

Daniel MacKinlay

Daniel Edward Pagendam

Petra Kuhnert

CoRR, 2024

Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families.

[BibT_eX]

[DOI]

Dino Sejdinovic

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Stochastic gradient updates yield deep equilibrium kernels.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

Earth Movers in The Big Data Era: A Review of Optimal Transport in Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Squared Neural Families: A New Class of Tractable Density Models.

[BibT_eX]

[DOI]

Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep equilibrium models as estimators for continuous latent variables.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning.

[BibT_eX]

[DOI]

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Declarative nets that are equilibrium models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Gaussian Process Bandits with Aggregated Feedback.

[BibT_eX]

[DOI]

Mengyan Zhang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks.

[BibT_eX]

[DOI]

Christopher van der Heide

Tim Pearce

Fred Roosta

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Results on infinitely wide multi-layer perceptrons

[BibT_eX]

[DOI]

PhD thesis, 2020

2019

Richer priors for infinitely wide multi-layer perceptrons.

[BibT_eX]

[DOI]

Fred Roosta

CoRR, 2019

Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Exchangeability and Kernel Invariance in Trained MLPs.

[BibT_eX]

[DOI]

Fred (Farbod) Roosta

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Invariance of Weight Distributions in Rectified MLPs.

[BibT_eX]

[DOI]

Farbod Roosta-Khorasani