3 papers
cs.CV2026
Feature-Space Generative Models for One-Shot Class-Incremental Learning
Jack Foster, Kirill Paramonov, Mete Ozay +1
Few-shot class-incremental learning (FSCIL) is a paradigm where a model, initially trained on a dataset of base classes, must adapt to an expanding problem space by recognizing nov…
cs.CV2025
Twist and Compute: The Cost of Pose in 3D Generative Diffusion
Kyle Fogarty, Jack Foster, Boqiao Zhang +2
Despite their impressive results, large-scale image-to-3D generative models remain opaque in their inductive biases. We identify a significant limitation in image-conditioned 3D ge…
cs.LG2024
Learning to Forget using Hypernetworks
Jose Miguel Lara Rangel, Stefan Schoepf, Jack Foster +2
Machine unlearning is gaining increasing attention as a way to remove adversarial data poisoning attacks from already trained models and to comply with privacy and AI regulations.…