Ondrej Bohdal
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Flexible Dataset Distillation: Learn Labels Instead of Images
O Bohdal, Y Yang, T Hospedales
NeurIPS 2020 Workshop on Meta-Learning, 2020
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error
O Bohdal, Y Yang, T Hospedales
TMLR 2023, 2021
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization
O Bohdal, Y Yang, T Hospedales
NeurIPS 2021, 2021
PASHA: Efficient HPO and NAS with Progressive Resource Allocation
O Bohdal, L Balles, M Wistuba, B Ermis, C Archambeau, G Zappella
ICLR 2023, 2022
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models
Y Zong, O Bohdal, T Yu, Y Yang, T Hospedales
ICML 2024, 2024
Feed-Forward Latent Domain Adaptation
O Bohdal, D Li, SX Hu, T Hospedales
WACV 2024, 2022
A Channel Coding Benchmark for Meta-Learning
R Li, O Bohdal, R Mishra, H Kim, D Li, N Lane, T Hospedales
NeurIPS 2021 (Datasets and Benchmarks), 2021
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn
O Bohdal, Y Tian, Y Zong, R Chavhan, D Li, H Gouk, L Guo, ...
CVPR 2023, 2023
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis
R Dutt, O Bohdal, SA Tsaftaris, T Hospedales
ICLR 2024, 2023
Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks
M Ferianc, O Bohdal, T Hospedales, M Rodrigues
TMLR 2024, 2023
Label Calibration for Semantic Segmentation Under Domain Shift
O Bohdal, D Li, T Hospedales
ICLR 2023 Workshop on Pitfalls of limited data and computation for …, 2023
Feed-Forward Source-Free Domain Adaptation via Class Prototypes
O Bohdal, D Li, T Hospedales
ECCV 2022 Workshop on Out of Distribution Generalization in Computer Vision …, 2022
Fairness in AI and Its Long-Term Implications on Society
O Bohdal, T Hospedales, PHS Torr, F Barez
Stanford Existential Risks Conference 2023, 2023
MemControl: Mitigating Memorization in Medical Diffusion Models via Automated Parameter Selection
R Dutt, P Sanchez, O Bohdal, SA Tsaftaris, T Hospedales
arXiv preprint arXiv:2405.19458, 2024
VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning
Y Zong, O Bohdal, T Hospedales
arXiv preprint arXiv:2403.13164, 2024
Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted
R Chavhan, O Bohdal, Y Zong, D Li, T Hospedales
arXiv preprint arXiv:2406.18566, 2024
Meta-learning algorithms and applications
O Bohdal
The University of Edinburgh, 2024
On the Limitations of General Purpose Domain Generalisation Methods
H Gouk, O Bohdal, D Li, T Hospedales
arXiv e-prints, arXiv: 2202.00563, 2022
Data Study Group Final Report: SenSat
T Allam, O Bohdal, N Dong, I Erofeev, Q Hu, J Kuehnert, PM Laribière, ...
Zenodo, 2020
Penalizing Confident Neural Networks
O Bohdal
University of Edinburgh, 2018
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