Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. - Jonathan Gordon 003; John Bronskill; Matthias Bauer 001; Sebastian Nowozin; Richard E. Turner (CoRR, 2018)

Meta-Learning Probabilistic Inference for Prediction. - Jonathan Gordon 003; John Bronskill; Matthias Bauer 001; Sebastian Nowozin; Richard E. Turner (ICLR (Poster), 2019)

Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes. - James Requeima; Jonathan Gordon 003; John Bronskill; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2019)

TaskNorm: Rethinking Batch Normalization for Meta-Learning. - John Bronskill; Jonathan Gordon 003; James Requeima; Sebastian Nowozin; Richard E. Turner (ICML, 2020)

Data and computation efficient meta-learning. - John Bronskill (2020)

ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition. - Daniela Massiceti; Luisa M. Zintgraf; John Bronskill; Lida Theodorou; Matthew Tobias Harris; Edward Cutrell; Cecily Morrison; Katja Hofmann; Simone Stumpf (ICCV, 2021)

Memory Efficient Meta-Learning with Large Images. - John Bronskill; Daniela Massiceti; Massimiliano Patacchiola; Katja Hofmann; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2021)

FS-Mol: A Few-Shot Learning Dataset of Molecules. - Megan Stanley; John Bronskill; Krzysztof Maziarz; Hubert Misztela; Jessica Lanini; Marwin H. S. Segler; Nadine Schneider; Marc Brockschmidt (NeurIPS Datasets and Benchmarks, 2021)

Adversarial Attacks are a Surprisingly Strong Baseline for Poisoning Few-Shot Meta-Learners. - Elre T. Oldewage; John Bronskill; Richard E. Turner (ICBINB, 2022)

Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification. - Massimiliano Patacchiola; John Bronskill; Aliaksandra Shysheya; Katja Hofmann; Sebastian Nowozin; Richard E. Turner (NeurIPS, 2022)

Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks. - Samyadeep Basu; Megan Stanley; John Bronskill; Soheil Feizi; Daniela Massiceti (ICLR, 2023)

FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification. - Aliaksandra Shysheya; John Bronskill; Massimiliano Patacchiola; Sebastian Nowozin; Richard E. Turner (ICLR, 2023)

On the Efficacy of Differentially Private Few-shot Image Classification. - Marlon Tobaben; Aliaksandra Shysheya; John Bronskill; Andrew Paverd; Shruti Tople; Santiago Zanella-Béguelin; Richard E. Turner; Antti Honkela (Trans. Mach. Learn. Res., 2023)

SportsNGEN: Sustained Generation of Realistic Multi-Player Sports Gameplay. - Lachlan Thorpe; Lewis Bawden; Karanjot Vendal; John Bronskill; Richard E. Turner (icSPORTS, 2024)

LLM Processes: Numerical Predictive Distributions Conditioned on Natural Language. - James Requeima; John Bronskill; Dami Choi; Richard E. Turner; David Kristjanson Duvenaud (NeurIPS, 2024)

SportsNGEN: Sustained Generation of Multi-player Sports Gameplay. - Lachlan Thorpe; Lewis Bawden; Karanjot Vendal; John Bronskill; Richard E. Turner (CoRR, 2024)

JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMs. - Aliaksandra Shysheya; John Bronskill; James Requeima; Shoaib Ahmed Siddiqui; Javier Gonzalez; David Duvenaud; Richard E. Turner (CoRR, 2025)