Timothy Hospedales
Professor
Researches machine learning, including meta-learning, transfer learning and data-efficient learning for computer vision.
Timothy Hospedales's lab at Edinburgh works on efficient training & inference. 44 papers since 2023, 33 at top venues, mostly ICLR and CVPR. 9 PhD students. 15 alumni.
At a glance
- papers, 2023–2026
- 11/ year
- at T1 venues
- 75%
- PhD students
- 9
- MS students
- 0
- alumni listed
- 15
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 5 papers2025 · T1 4
- 16 papers2024 · T1 12
- 23 papers2023 · T1 17
T1 venuesOtherVenues: ICLR, CVPR, TMLR, WACV, ICML
Research focuspaper titles that use each topic's words
- Efficient training & inference7 papers
- meta-learning1 paper
- data-efficient1 paper
- transfer learning0 papers
- transfer0 papers
Paper list
From the lab homepage.
20255 papers
- AAAI (T1)A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning
- ICLR (T1)ConceptPrune: Concept Editing in Diffusion Models via Skilled Neuron Pruning
- ICLR (T1)LIFT: Learning to Fine-Tune via Bayesian Parameter-Efficient Meta Fine-Tuning
- WACVMemcontrol: Mitigating memorization in medical diffusion models via automated parameter selection
- ICLR (T1)VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning
202416 papers
- NeurIPS (T1)A Bayesian Approach to Data Point Selection
- ICLR (T1)A Hierarchical Bayesian Model for Few-Shot Meta Learning
- CVPR (T1)DemoFusion: Democratising High-Resolution Image Generation With No $$$
- TMLR (T1)Evaluating the evaluators: Are validation methods for few-shot learning fit for purpose?
- IEEE AccessFairness Meets Cross-Domain Learning: A Benchmark of Models and Metrics
- ICLR (T1)FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
- WACVFeed-Forward Latent Domain Adaptation
- ICML (T1)Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations
- WACVMeta-Learned Kernel For Blind Super-Resolution Kernel Estimation
- EMNLP (T1)MobileQuant: Mobile-friendly Quantization for On-device Language Models
- TMLR (T1)Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks
- ICLR (T1)Neural Fine-Tuning Search for Few-Shot Learning
202323 papers
- WACVAccelerating Self-Supervised Learning via Efficient Training Strategies
- ICLR (T1)Amortised Invariance Learning for Contrastive Self-Supervision
- CVPR (T1)An Erudite Fine-Grained Visual Classification Model
- ICANNAn Evaluation of Self-Supervised Learning for Portfolio Diversification
- NeurIPS (T1)BayesTune: Bayesian Sparse Deep Model Fine-tuning
- AutoMLBetter Practices for Domain Adaptation
- ICLR (T1)ChiroDiff: Modelling chirographic data with Diffusion Models
- ICLR (T1)Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach
- NeurIPS (T1)FedL2P: Federated Learning to Personalize
- ICLR (T1)Learning where and when to reason in neuro-symbolic inference
- ICLR (T1)MEDFAIR: Benchmarking Fairness for Medical Imaging
- CVPR (T1)Meta Omnium: A Benchmark for General-Purpose Learning-to-learn
Where alumni went15 listed, 0% to industry
Industry 0Academia 10
Also to
- University of Edinburgh
- ETH Zurich
- Fudan University
Apply to EdinburghFall 2027
Not announced yet
Informatics PhD
- Round
- Rolling (funding consideration)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- none
Not yet confirmed for this intake.
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