Benjamin Bloem-Reddy

According to our database, Benjamin Bloem-Reddy authored at least 17 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Debiased Counterfactual Generation via Flow Matching from Observations.

Hugh Dance, Johnny Xi, Peter Orbanz, Benjamin Bloem-Reddy

CoRR, May, 2026

2025

CN-SBM: Categorical Block Modelling For Primary and Residual Copy Number Variation.

Kevin Lam, William Daniels, J. Maxwell Douglas, Daniel Lai, Samuel Aparicio, Benjamin Bloem-Reddy, Yongjin Park

Proceedings of the 20th Machine Learning in Computational Biology (MLCB), 2025

Distinguishing Cause from Effect with Causal Velocity Models.

Johnny Xi, Hugh Dance, Peter Orbanz, Benjamin Bloem-Reddy

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Identifying Metric Structures of Deep Latent Variable Models.

Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Mixed variational flows for discrete variables.

Gian Carlo Diluvi, Benjamin Bloem-Reddy, Trevor Campbell

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

On Neural Process Pooling Operator Choice and Posterior Calibration.

Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood

Proceedings of the 37th Canadian Conference on Artificial Intelligence, 2024

2023

Indeterminacy in Generative Models: Characterization and Strong Identifiability.

Quanhan Xi, Benjamin Bloem-Reddy

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

2022

Indeterminacy in Latent Variable Models: Characterization and Strong Identifiability.

Quanhan Xi, Benjamin Bloem-Reddy

CoRR, 2022

2021

Lossy Compression for Lossless Prediction.

Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Probabilistic Symmetries and Invariant Neural Networks.

Benjamin Bloem-Reddy, Yee Whye Teh

J. Mach. Learn. Res., 2020

Uncertainty in Neural Processes.

Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood

CoRR, 2020

On the Benefits of Invariance in Neural Networks.

Clare Lyle, Mark van der Wilk, Marta Kwiatkowska, Yarin Gal, Benjamin Bloem-Reddy

CoRR, 2020

2019

Probabilistic symmetry and invariant neural networks.

Benjamin Bloem-Reddy, Yee Whye Teh

CoRR, 2019

2018

Sequential sampling of Gaussian process latent variable models.

Martin Tegner, Benjamin Bloem-Reddy, Stephen J. Roberts

CoRR, 2018

Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks.

Benjamin Bloem-Reddy, Adam Foster, Emile Mathieu, Yee Whye Teh

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

2017

Preferential Attachment and Vertex Arrival Times.

Benjamin Bloem-Reddy, Peter Orbanz

CoRR, 2017

2016

Slice Sampling on Hamiltonian Trajectories.

Benjamin Bloem-Reddy, John P. Cunningham

Proceedings of the 33nd International Conference on Machine Learning, 2016