Matthew Ashman

24 papers A* 6A 1Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Meta-Learning Approach to Bayesian Causal Discovery. ICLR Anish Dhir, Matthew Ashman, James Requeima, Mark van der Wilk
2025	A*	`conf`	Gridded Transformer Neural Processes for Spatio-Temporal Data. ICML Matthew Ashman, Cristiana Diaconu, Eric Langezaal, Adrian Weller, Richard E. Turner
2025	J	`jnl`	Tighter sparse variational Gaussian processes. CoRR Thang D. Bui, Matthew Ashman, Richard E. Turner
2025	J	`jnl`	Tighter sparse variational Gaussian processes. Trans. Mach. Learn. Res. Thang D. Bui, Matthew Ashman, Richard E. Turner
2024	J	`jnl`	A Meta-Learning Approach to Bayesian Causal Discovery. CoRR Anish Dhir, Matthew Ashman, James Requeima, Mark van der Wilk
2024	A*	`conf`	Approximately Equivariant Neural Processes. NeurIPS Matthew Ashman, Cristiana Diaconu, Adrian Weller, Wessel P. Bruinsma, Richard E. Turner
2024	J	`jnl`	Approximately Equivariant Neural Processes. CoRR Matthew Ashman, Cristiana Diaconu, Adrian Weller, Wessel P. Bruinsma, Richard E. Turner
2024	J	`jnl`	Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data. CoRR Matthew Ashman, Cristiana Diaconu, Eric Langezaal, Adrian Weller, Richard E. Turner
2024	—	`conf`	In-Context In-Context Learning with Transformer Neural Processes. AABI Matthew Ashman, Cristiana Diaconu, Adrian Weller, Richard E. Turner
2024	J	`jnl`	In-Context In-Context Learning with Transformer Neural Processes. CoRR Matthew Ashman, Cristiana Diaconu, Adrian Weller, Richard E. Turner
2024	A*	`conf`	Noise-Aware Differentially Private Regression via Meta-Learning. NeurIPS Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben, Antti Honkela, Richard E. Turner
2024	J	`jnl`	Noise-Aware Differentially Private Regression via Meta-Learning. CoRR Ossi Räisä, Stratis Markou, Matthew Ashman, Wessel P. Bruinsma, Marlon Tobaben, Antti Honkela, Richard E. Turner
2024	A*	`conf`	Translation Equivariant Transformer Neural Processes. ICML Matthew Ashman, Cristiana Diaconu, Junhyuck Kim, Lakee Sivaraya, Stratis Markou, James Requeima, Wessel P. Bruinsma, Richard E. Turner
2024	J	`jnl`	Translation Equivariant Transformer Neural Processes. CoRR Matthew Ashman, Cristiana Diaconu, Junhyuck Kim, Lakee Sivaraya, Stratis Markou, James Requeima, Wessel P. Bruinsma, Richard E. Turner
2023	J	`jnl`	Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning. CoRR Matthew Ashman, Tommy Rochussen, Adrian Weller
2023	A*	`conf`	Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. ICLR Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
2023	J	`jnl`	Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning. CoRR Matthew Ashman, Chao Ma, Agrin Hilmkil, Joel Jennings, Cheng Zhang
2023	J	`jnl`	Differentially private partitioned variational inference. Trans. Mach. Learn. Res. Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
2023	—	`conf`	GeValDi: Generative Validation of Discriminative Models. Tiny Papers @ ICLR Vivek Palaniappan, Matthew Ashman, Katherine M. Collins, Juyeon Heo, Adrian Weller, Umang Bhatt
2022	J	`jnl`	Differentially private partitioned variational inference. CoRR Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E. Turner, Antti Honkela
2022	J	`jnl`	Partitioned Variational Inference: A Framework for Probabilistic Federated Learning. CoRR Matthew Ashman, Thang D. Bui, Cuong V. Nguyen, Efstratios Markou, Adrian Weller, Siddharth Swaroop, Richard E. Turner
2021	J	`jnl`	Do Concept Bottleneck Models Learn as Intended? CoRR Andrei Margeloiu, Matthew Ashman, Umang Bhatt, Yanzhi Chen, Mateja Jamnik, Adrian Weller
2021	A	`conf`	Scalable Gaussian Process Variational Autoencoders. AISTATS Metod Jazbec, Matthew Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch
2020	J	`jnl`	Sparse Gaussian Process Variational Autoencoders. CoRR Matthew Ashman, Jonathan So, William Tebbutt, Vincent Fortuin, Michael Pearce, Richard E. Turner