Joy, Tom

7 publications

TMLR 2024 MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection Kemal Oksuz, Selim Kuzucu, Tom Joy, Puneet K. Dokania

NeurIPS 2024 What Makes and Breaks Safety Fine-Tuning? a Mechanistic Study Samyak Jain, Ekdeep Singh Lubana, Kemal Oksuz, Tom Joy, Philip H.S. Torr, Amartya Sanyal, Puneet K. Dokania

ICMLW 2024 What Makes and Breaks Safety Fine-Tuning? a Mechanistic Study Samyak Jain, Ekdeep Singh Lubana, Kemal Oksuz, Tom Joy, Philip Torr, Amartya Sanyal, Puneet K. Dokania

AAAI 2023 Sample-Dependent Adaptive Temperature Scaling for Improved Calibration Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania

CVPR 2023 Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration Kemal Oksuz, Tom Joy, Puneet K. Dokania

ICLR 2022 Learning Multimodal VAEs Through Mutual Supervision Tom Joy, Yuge Shi, Philip Torr, Tom Rainforth, Sebastian M Schmon, Siddharth N

ICLR 2021 Capturing Label Characteristics in VAEs Tom Joy, Sebastian Schmon, Philip Torr, Siddharth N, Tom Rainforth