Benjamin Bloem-Reddy

22 papers A* 4A 3Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	CN-SBM: Categorical Block Modelling For Primary and Residual Copy Number Variation. MLCB Kevin Lam, William Daniels, J. Maxwell Douglas, Daniel Lai, Samuel Aparicio, Benjamin Bloem-Reddy, Yongjin Park
2025	J	`jnl`	CN-SBM: Categorical Block Modelling For Primary and Residual Copy Number Variation. CoRR Kevin Lam, William Daniels, J. Maxwell Douglas, Daniel Lai, Samuel Aparicio, Benjamin Bloem-Reddy, Yongjin Park
2025	A*	`conf`	Distinguishing Cause from Effect with Causal Velocity Models. ICML Johnny Xi, Hugh Dance, Peter Orbanz, Benjamin Bloem-Reddy
2025	J	`jnl`	Distinguishing Cause from Effect with Causal Velocity Models. CoRR Johnny Xi, Hugh Dance, Peter Orbanz, Benjamin Bloem-Reddy
2025	A*	`conf`	Identifying Metric Structures of Deep Latent Variable Models. ICML Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
2025	J	`jnl`	Identifying metric structures of deep latent variable models. CoRR Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
2024	A	`conf`	Mixed variational flows for discrete variables. AISTATS Gian Carlo Diluvi, Benjamin Bloem-Reddy, Trevor Campbell
2024	—	`conf`	On Neural Process Pooling Operator Choice and Posterior Calibration. Canadian AI Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood
2023	A	`conf`	Indeterminacy in Generative Models: Characterization and Strong Identifiability. AISTATS Quanhan Xi, Benjamin Bloem-Reddy
2023	J	`jnl`	Mixed Variational Flows for Discrete Variables. CoRR Gian Carlo Diluvi, Benjamin Bloem-Reddy, Trevor Campbell
2022	J	`jnl`	Indeterminacy in Latent Variable Models: Characterization and Strong Identifiability. CoRR Quanhan Xi, Benjamin Bloem-Reddy
2021	A*	`conf`	Lossy Compression for Lossless Prediction. NeurIPS Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison
2021	J	`jnl`	Lossy Compression for Lossless Prediction. CoRR Yann Dubois, Benjamin Bloem-Reddy, Karen Ullrich, Chris J. Maddison
2020	J	`jnl`	On the Benefits of Invariance in Neural Networks. CoRR Clare Lyle, Mark van der Wilk, Marta Kwiatkowska, Yarin Gal, Benjamin Bloem-Reddy
2020	J	`jnl`	Probabilistic Symmetries and Invariant Neural Networks. J. Mach. Learn. Res. Benjamin Bloem-Reddy, Yee Whye Teh
2020	J	`jnl`	Uncertainty in Neural Processes. CoRR Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood
2019	J	`jnl`	Probabilistic symmetry and invariant neural networks. CoRR Benjamin Bloem-Reddy, Yee Whye Teh
2018	A	`conf`	Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks. UAI Benjamin Bloem-Reddy, Adam Foster, Emile Mathieu, Yee Whye Teh
2018	J	`jnl`	Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks. CoRR Benjamin Bloem-Reddy, Adam Foster, Emile Mathieu, Yee Whye Teh
2018	J	`jnl`	Sequential sampling of Gaussian process latent variable models. CoRR Martin Tegner, Benjamin Bloem-Reddy, Stephen J. Roberts
2017	J	`jnl`	Preferential Attachment and Vertex Arrival Times. CoRR Benjamin Bloem-Reddy, Peter Orbanz
2016	A*	`conf`	Slice Sampling on Hamiltonian Trajectories. ICML Benjamin Bloem-Reddy, John P. Cunningham