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ORCIDOndrej Bohdal
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2020 – today
- 2024
[j2]Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues:
Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks. Trans. Mach. Learn. Res. 2024 (2024)- [c7]Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy M. Hospedales:
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis. ICLR 2024 - [c6]Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, Timothy M. Hospedales:
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models. ICML 2024 - [c5]Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Feed-Forward Latent Domain Adaptation. WACV 2024: 8475-8484 - [i18]Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, Yongxin Yang, Timothy M. Hospedales:
Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models. CoRR abs/2402.02207 (2024) - [i17]Yongshuo Zong, Ondrej Bohdal, Timothy M. Hospedales:
VL-ICL Bench: The Devil in the Details of Benchmarking Multimodal In-Context Learning. CoRR abs/2403.13164 (2024) - [i16]Raman Dutt, Pedro Sanchez, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy M. Hospedales:
MemControl: Mitigating Memorization in Medical Diffusion Models via Automated Parameter Selection. CoRR abs/2405.19458 (2024) - [i15]Ruchika Chavhan, Ondrej Bohdal, Yongshuo Zong, Da Li, Timothy M. Hospedales:
Memorized Images in Diffusion Models share a Subspace that can be Located and Deleted. CoRR abs/2406.18566 (2024) - [i14]Raman Dutt, Pedro Sanchez, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy M. Hospedales:
Capacity Control is an Effective Memorization Mitigation Mechanism in Text-Conditional Diffusion Models. CoRR abs/2410.22149 (2024) - [i13]Donald Shenaj, Ondrej Bohdal, Mete Ozay, Pietro Zanuttigh, Umberto Michieli:
LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image Generation. CoRR abs/2412.05148 (2024) - 2023
- [j1]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error. Trans. Mach. Learn. Res. 2023 (2023) - [c4]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CVPR 2023: 7693-7703 - [c3]Ondrej Bohdal, Lukas Balles, Martin Wistuba, Beyza Ermis, Cédric Archambeau, Giovanni Zappella:
PASHA: Efficient HPO and NAS with Progressive Resource Allocation. ICLR 2023 - [i12]Ondrej Bohdal, Timothy M. Hospedales, Philip H. S. Torr, Fazl Barez:
Fairness in AI and Its Long-Term Implications on Society. CoRR abs/2304.09826 (2023) - [i11]Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy M. Hospedales:
Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. CoRR abs/2305.07625 (2023) - [i10]Martin Ferianc, Ondrej Bohdal, Timothy M. Hospedales, Miguel R. D. Rodrigues:
Impact of Noise on Calibration and Generalisation of Neural Networks. CoRR abs/2306.17630 (2023) - [i9]Ondrej Bohdal, Da Li, Timothy M. Hospedales:
Feed-Forward Source-Free Domain Adaptation via Class Prototypes. CoRR abs/2307.10787 (2023) - [i8]Ondrej Bohdal, Da Li, Timothy M. Hospedales:
Label Calibration for Semantic Segmentation Under Domain Shift. CoRR abs/2307.10842 (2023) - [i7]Raman Dutt, Ondrej Bohdal, Sotirios A. Tsaftaris, Timothy M. Hospedales:
FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis. CoRR abs/2310.05055 (2023) - 2022
- [i6]Ondrej Bohdal, Lukas Balles, Beyza Ermis, Cédric Archambeau, Giovanni Zappella:
PASHA: Efficient HPO with Progressive Resource Allocation. CoRR abs/2207.06940 (2022) - [i5]Ondrej Bohdal, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Feed-Forward Source-Free Latent Domain Adaptation via Cross-Attention. CoRR abs/2207.07624 (2022) - 2021
- [c2]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. NeurIPS 2021: 22234-22246 - [c1]Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales:
A Channel Coding Benchmark for Meta-Learning. NeurIPS Datasets and Benchmarks 2021 - [i4]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error. CoRR abs/2106.09613 (2021) - [i3]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. CoRR abs/2106.10575 (2021) - [i2]Rui Li, Ondrej Bohdal, Rajesh K. Mishra, Hyeji Kim, Da Li, Nicholas D. Lane, Timothy M. Hospedales:
A Channel Coding Benchmark for Meta-Learning. CoRR abs/2107.07579 (2021) - 2020
- [i1]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Flexible Dataset Distillation: Learn Labels Instead of Images. CoRR abs/2006.08572 (2020)
Coauthor Index
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