John Bronskill

27 papers A* 8Journal 14Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Stroke Patches: Customizable Artistic Image Styling Using Regression. CoRR Ian Jaffray, John Bronskill
2025	J	`jnl`	JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMs. CoRR Aliaksandra Shysheya, John Bronskill, James Requeima, Shoaib Ahmed Siddiqui, Javier González, David Duvenaud, Richard E. Turner
2024	A*	`conf`	LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language. NeurIPS James Requeima, John Bronskill, Dami Choi, Richard E. Turner, David Kristjanson Duvenaud
2024	J	`jnl`	LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language. CoRR James Requeima, John Bronskill, Dami Choi, Richard E. Turner, David Duvenaud
2024	J	`jnl`	SportsNGEN: Sustained Generation of Multi-player Sports Gameplay. CoRR Lachlan Thorpe, Lewis Bawden, Karanjot Vendal, John Bronskill, Richard E. Turner
2024	—	`conf`	SportsNGEN: Sustained Generation of Realistic Multi-Player Sports Gameplay. icSPORTS Lachlan Thorpe, Lewis Bawden, Karanjot Vendal, John Bronskill, Richard E. Turner
2023	A*	`conf`	FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. ICLR Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E. Turner
2023	A*	`conf`	Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks. ICLR Samyadeep Basu, Megan Stanley, John Bronskill, Soheil Feizi, Daniela Massiceti
2023	J	`jnl`	On the Efficacy of Differentially Private Few-shot Image Classification. CoRR Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard E. Turner, Antti Honkela
2023	J	`jnl`	On the Efficacy of Differentially Private Few-shot Image Classification. Trans. Mach. Learn. Res. Marlon Tobaben, Aliaksandra Shysheya, John Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Béguelin, Richard E. Turner, Antti Honkela
2022	—	`conf`	Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners. ICBINB Elre T. Oldewage, John Bronskill, Richard E. Turner
2022	J	`jnl`	Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners. CoRR Elre T. Oldewage, John Bronskill, Richard E. Turner
2022	A*	`conf`	Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. NeurIPS Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
2022	J	`jnl`	Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. CoRR Massimiliano Patacchiola, John Bronskill, Aliaksandra Shysheya, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
2022	J	`jnl`	FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. CoRR Aliaksandra Shysheya, John Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E. Turner
2021	—	`conf`	FS-Mol: A Few-Shot Learning Dataset of Molecules. NeurIPS Datasets and Benchmarks Megan Stanley, John Bronskill, Krzysztof Maziarz, Hubert Misztela, Jessica Lanini, Marwin H. S. Segler, Nadine Schneider, Marc Brockschmidt
2021	A*	`conf`	Memory Efficient Meta-Learning with Large Images. NeurIPS John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
2021	J	`jnl`	Memory Efficient Meta-Learning with Large Images. CoRR John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner
2021	A*	`conf`	ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. ICCV Daniela Massiceti, Luisa M. Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
2021	J	`jnl`	ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. CoRR Daniela Massiceti, Luisa M. Zintgraf, John Bronskill, Lida Theodorou, Matthew Tobias Harris, Edward Cutrell, Cecily Morrison, Katja Hofmann, Simone Stumpf
2020	—	`—`	Data and computation efficient meta-learning. John Bronskill
2020	A*	`conf`	TaskNorm: Rethinking Batch Normalization for Meta-Learning. ICML John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
2020	J	`jnl`	TaskNorm: Rethinking Batch Normalization for Meta-Learning. CoRR John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
2019	J	`jnl`	Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes. CoRR James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
2019	A*	`conf`	Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes. NeurIPS James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
2019	—	`conf`	Meta-Learning Probabilistic Inference for Prediction. ICLR (Poster) Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner
2018	J	`jnl`	Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. CoRR Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner