Reducing catastrophic forgetting when evolving neural networks. - Joseph Early (CoRR, 2019)

Non-Asimov Explanations Regulating AI through Transparency. - Chris Reed 002; Keri Grieman; Joseph Early (CoRR, 2021)

Revisiting Deep Fisher Vectors: Using Fisher Information to Improve Object Classification. - Sarah Ahmed; Tayyaba Azim; Joseph Early; Sarvapali D. Ramchurn (BMVC, 2022)

Model Agnostic Interpretability for Multiple Instance Learning. - Joseph Early; Christine Evers; Sarvapali D. Ramchurn (ICLR, 2022)

Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning. - Joseph Early; Tom Bewley; Christine Evers; Sarvapali D. Ramchurn (NeurIPS, 2022)

Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification. - Joseph Early; Ying-Jung Deweese; Christine Evers; Sarvapali D. Ramchurn (CoRR, 2022)

Inferring Player Location in Sports Matches: Multi-Agent Spatial Imputation from Limited Observations. - Gregory Everett; Ryan J. Beal; Tim Matthews; Joseph Early; Timothy J. Norman; Sarvapali D. Ramchurn (AAMAS, 2023)

Inherently Interpretable Time Series Classification via Multiple Instance Learning. - Joseph Early; Gavin K. C. Cheung; Kurt Cutajar; Hanting Xie; Jas Kandola; Niall Twomey (ICLR, 2024)