Hartnup disease by Patel A, Prabhu A

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GDumb: A simple approach that questions our progress in continual learning by Prabhu, A, Torr, PHS, Dokania, PK

Astrophysical constraints on decaying dark gravitons by Law-Smith, JAP, Obied, G, Prabhu, A, Vafa, C

Corrective machine unlearning by Goel, S, Prabhu, A, Torr, P, Kumaraguru, P, Sanyal, A

RanDumb: a simple approach that questions the efficacy of continual representation learning by Prabhu, A, Sinha, S, Kumaraguru, P, Torr, PHS, Sener, O, Dokania, PK

Lifelong benchmarks: efficient model evaluation in an era of rapid progress by Prabhu, A, Udandarao, V, Torr, PHS, Bethge, M, Bibi, A, Albanie, S

Pre-training concept frequency is predictive of CLIP zero-shot performance by Udandarao, V, Prabhu, A, Torr, PHS, Bibi, A, Albanie, S, Bethge, M

Effectiveness  of a Disease Management Program (DMP) in controlling the progression of Chronic Kidney Disease among hypertensives and diabetics. [version 3; peer review: 2 approved... by Baby S Nayak, Shankar Prasad Nagaraju, Ravindra Prabhu A., Shreemathi S Mayya, Leena Sequira

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Rapid adaptation in online continual learning: are we evaluating it right? by Hammoud, HAAK, Prabhu, A, Lim, S-N, Torr, PHS, Bibi, A, Ghanem, B

kNN-CLIP: retrieval enables training-free segmentation on continually expanding large vocabularies by Gui, Z, Sun, S, Li, R, Yuan, J, An, Z, Roth, K, Prabhu, A, Torr, P

Computationally budgeted continual learning: what does matter? by Prabhu, A, Hammoud, HAAK, Dokania, P, Torr, P, Lim, SN, Ghanem, B, Bibi, A

No "zero-shot" without exponential data: pretraining concept frequency determines multimodal model performance by Udandarao, V, Prabhu, A, Ghosh, A, Sharma, Y, Torr, PHS, Bibi, A, Albanie, S, Bethge, M

Real-time evaluation in online continual learning: a new hope by Ghunaim, Y, Bibi, A, Alhamoud, K, Alfarra, M, Hammoud, HAAK, Prabhu, A, Torr, PHS, Ghanem, B