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ORCIDTimothy M. Hospedales
Person information
- affiliation: Queen Mary University of London, UK
- affiliation (PhD 2008): University of Edinburgh, UK
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2020 – today
- 2023
[j35]Peng Xu
, Timothy M. Hospedales, Qiyue Yin, Yi-Zhe Song, Tao Xiang, Liang Wang:
Deep Learning for Free-Hand Sketch: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 285-312 (2023)- [c139]Mustafa Taha Koçyigit, Timothy M. Hospedales, Hakan Bilen:
Accelerating Self-Supervised Learning via Efficient Training Strategies. WACV 2023: 5643-5653 - [i122]Minyoung Kim, Da Li, Timothy M. Hospedales:
Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach. CoRR abs/2302.12047 (2023) - [i121]Ruchika Chavhan, Henry Gouk, Jan Stuehmer, Calum Heggan, Mehrdad Yaghoobi, Timothy M. Hospedales:
Amortised Invariance Learning for Contrastive Self-Supervision. CoRR abs/2302.12712 (2023) - 2022
- [j34]Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, Amos J. Storkey:
Meta-Learning in Neural Networks: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5149-5169 (2022) - [j33]Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales:
Self-Supervised Representation Learning: Introduction, advances, and challenges. IEEE Signal Process. Mag. 39(3): 42-62 (2022) - [j32]Marija Jegorova, Stéphane Doncieux, Timothy M. Hospedales:
Behavioral Repertoire via Generative Adversarial Policy Networks. IEEE Trans. Cogn. Dev. Syst. 14(4): 1344-1355 (2022) - [c138]Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M. Hospedales, Yi-Zhe Song:
Towards Unsupervised Sketch-based Image Retrieval. BMVC 2022: 224 - [c137]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Why Do Self-Supervised Models Transfer? On the Impact of Invariance on Downstream Tasks. BMVC 2022: 509 - [c136]Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales:
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CVPR 2022: 9058-9067 - [c135]Calum Heggan, Sam Budgett, Timothy M. Hospedales, Mehrdad Yaghoobi:
MetaAudio: A Few-Shot Audio Classification Benchmark. ICANN (1) 2022: 219-230 - [c134]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
SketchODE: Learning neural sketch representation in continuous time. ICLR 2022 - [c133]Lucas Deecke, Timothy M. Hospedales, Hakan Bilen:
Visual Representation Learning over Latent Domains. ICLR 2022 - [c132]Haebeom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy M. Hospedales, Sung Ju Hwang:
Online Hyperparameter Meta-Learning with Hypergradient Distillation. ICLR 2022 - [c131]Boyan Gao, Henry Gouk, Yongxin Yang, Timothy M. Hospedales:
Loss Function Learning for Domain Generalization by Implicit Gradient. ICML 2022: 7002-7016 - [c130]Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Fisher SAM: Information Geometry and Sharpness Aware Minimisation. ICML 2022: 11148-11161 - [c129]Miguel Jaques, Martin Asenov, Michael Burke, Timothy M. Hospedales:
Vision-based System Identification and 3D Keypoint Discovery using Dynamics Constraints. L4DC 2022: 316-329 - [i120]Da Li, Henry Gouk, Timothy M. Hospedales:
Finding lost DG: Explaining domain generalization via model complexity. CoRR abs/2202.00563 (2022) - [i119]Boyan Gao, Henry Gouk, Haebeom Lee, Timothy M. Hospedales:
Meta Mirror Descent: Optimiser Learning for Fast Convergence. CoRR abs/2203.02711 (2022) - [i118]Calum Heggan, Sam Budgett, Timothy M. Hospedales, Mehrdad Yaghoobi:
MetaAudio: A Few-Shot Audio Classification Benchmark. CoRR abs/2204.02121 (2022) - [i117]Shell Xu Hu, Da Li, Jan Stühmer, Minyoung Kim, Timothy M. Hospedales:
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference. CoRR abs/2204.07305 (2022) - [i116]Minyoung Kim, Da Li, Shell Xu Hu, Timothy M. Hospedales:
Fisher SAM: Information Geometry and Sharpness Aware Minimisation. CoRR abs/2206.04920 (2022) - [i115]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) - [i114]Ruchika Chavhan, Henry Gouk, Jan Stühmer, Timothy M. Hospedales:
HyperInvariances: Amortizing Invariance Learning. CoRR abs/2207.08304 (2022) - [i113]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Attacking Adversarial Defences by Smoothing the Loss Landscape. CoRR abs/2208.00862 (2022) - [i112]Yongshuo Zong, Yongxin Yang, Timothy M. Hospedales:
MEDFAIR: Benchmarking Fairness for Medical Imaging. CoRR abs/2210.01725 (2022) - [i111]Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales:
Federated Learning for Inference at Anytime and Anywhere. CoRR abs/2212.04084 (2022) - [i110]Mustafa Taha Koçyigit, Timothy M. Hospedales, Hakan Bilen:
Accelerating Self-Supervised Learning via Efficient Training Strategies. CoRR abs/2212.05611 (2022) - [i109]Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. CoRR abs/2212.07886 (2022) - 2021
- [j31]Qian Yu, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales:
Fine-Grained Instance-Level Sketch-Based Image Retrieval. Int. J. Comput. Vis. 129(2): 484-500 (2021) - [j30]Peng Xu, Kun Liu, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma, Jun Guo, Yi-Zhe Song:
Fine-Grained Instance-Level Sketch-Based Video Retrieval. IEEE Trans. Circuits Syst. Video Technol. 31(5): 1995-2007 (2021) - [j29]Peng Xu, Yongye Huang, Tongtong Yuan, Tao Xiang, Timothy M. Hospedales, Yi-Zhe Song, Liang Wang:
On Learning Semantic Representations for Large-Scale Abstract Sketches. IEEE Trans. Circuits Syst. Video Technol. 31(9): 3366-3379 (2021) - [j28]Anran Qi, Yulia Gryaditskaya, Jifei Song, Yongxin Yang, Yonggang Qi, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Toward Fine-Grained Sketch-Based 3D Shape Retrieval. IEEE Trans. Image Process. 30: 8595-8606 (2021) - [c128]Tianyuan Yu, Yongxin Yang, Da Li, Timothy M. Hospedales, Tao Xiang:
Simple and Effective Stochastic Neural Networks. AAAI 2021: 3252-3260 - [c127]Efthymia Tsamoura, Timothy M. Hospedales, Loizos Michael:
Neural-Symbolic Integration: A Compositional Perspective. AAAI 2021: 5051-5060 - [c126]Chenyang Zhao, Timothy M. Hospedales:
Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation. ACML 2021: 1237-1252 - [c125]Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya, Yannis Panagakis, Timothy M. Hospedales, Georgios Tzimiropoulos, Nicholas D. Lane, Maja Pantic:
Defensive Tensorization. BMVC 2021: 131 - [c124]Yuting Qiang, Yongxin Yang, Xueting Zhang, Yanwen Guo, Timothy M. Hospedales:
Tensor Composition Net for Visual Relationship Prediction. BMVC 2021: 434 - [c123]Miguel Jaques, Michael Burke, Timothy M. Hospedales:
NewtonianVAE: Proportional Control and Goal Identification From Pixels via Physical Latent Spaces. CVPR 2021: 4454-4463 - [c122]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
How Well Do Self-Supervised Models Transfer? CVPR 2021: 5414-5423 - [c121]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. CVPR 2021: 5672-5681 - [c120]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Cloud2Curve: Generation and Vectorization of Parametric Sketches. CVPR 2021: 7088-7097 - [c119]Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales:
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. ICCV 2021: 631-640 - [c118]Boyan Gao, Henry Gouk, Timothy M. Hospedales:
Searching for Robustness: Loss Learning for Noisy Classification Tasks. ICCV 2021: 6650-6659 - [c117]Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, Timothy M. Hospedales:
A Simple Feature Augmentation for Domain Generalization. ICCV 2021: 8866-8875 - [c116]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
Interpreting Knowledge Graph Relation Representation from Word Embeddings. ICLR 2021 - [c115]Henry Gouk, Timothy M. Hospedales, Massimiliano Pontil:
Distance-Based Regularisation of Deep Networks for Fine-Tuning. ICLR 2021 - [c114]Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy M. Hospedales:
Weight-covariance alignment for adversarially robust neural networks. ICML 2021: 3047-3056 - [c113]Adrian El Baz, Ihsan Ullah, Edesio Alcobaça, André C. P. L. F. de Carvalho, Hong Chen, Fabio Ferreira, Henry Gouk, Chaoyu Guan, Isabelle Guyon, Timothy M. Hospedales, Shell Hu, Mike Huisman, Frank Hutter, Zhengying Liu, Felix Mohr, Ekrem Öztürk, Jan N. van Rijn, Haozhe Sun, Xin Wang, Wenwu Zhu:
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification. NeurIPS (Competition and Demos) 2021: 80-96 - [c112]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. NeurIPS 2021: 22234-22246 - [c111]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 - [i108]Xueting Zhang, Debin Meng, Henry Gouk, Timothy M. Hospedales:
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition. CoRR abs/2101.02833 (2021) - [i107]Yiying Li, Wei Zhou, Huaimin Wang, Haibo Mi, Timothy M. Hospedales:
FedH2L: Federated Learning with Model and Statistical Heterogeneity. CoRR abs/2101.11296 (2021) - [i106]Boyan Gao, Henry Gouk, Timothy M. Hospedales:
Searching for Robustness: Loss Learning for Noisy Classification Tasks. CoRR abs/2103.00243 (2021) - [i105]Ayan Kumar Bhunia, Pinaki Nath Chowdhury, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting. CoRR abs/2103.13716 (2021) - [i104]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Cloud2Curve: Generation and Vectorization of Parametric Sketches. CoRR abs/2103.15536 (2021) - [i103]Conghui Hu, Yongxin Yang, Yunpeng Li, Timothy M. Hospedales, Yi-Zhe Song:
Towards Unsupervised Sketch-based Image Retrieval. CoRR abs/2105.08237 (2021) - [i102]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Meta-Calibration: Meta-Learning of Model Calibration Using Differentiable Expected Calibration Error. CoRR abs/2106.09613 (2021) - [i101]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter Optimization. CoRR abs/2106.10575 (2021) - [i100]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) - [i99]Miguel Jaques, Martin Asenov, Michael Burke, Timothy M. Hospedales:
Vision-based system identification and 3D keypoint discovery using dynamics constraints. CoRR abs/2109.05928 (2021) - [i98]Haebeom Lee, Hayeon Lee, Jaewoong Shin, Eunho Yang, Timothy M. Hospedales, Sung Ju Hwang:
Online Hyperparameter Meta-Learning with Hypergradient Distillation. CoRR abs/2110.02508 (2021) - [i97]Linus Ericsson, Henry Gouk, Chen Change Loy, Timothy M. Hospedales:
Self-Supervised Representation Learning: Introduction, Advances and Challenges. CoRR abs/2110.09327 (2021) - [i96]Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya, Yannis Panagakis, Timothy M. Hospedales, Georgios Tzimiropoulos, Nicholas D. Lane, Maja Pantic:
Defensive Tensorization. CoRR abs/2110.13859 (2021) - [i95]Minyoung Kim, Timothy M. Hospedales:
Gaussian Process Meta Few-shot Classifier Learning via Linear Discriminant Laplace Approximation. CoRR abs/2111.05392 (2021) - [i94]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks. CoRR abs/2111.11398 (2021) - 2020
- [j27]Ling Shao, Hubert P. H. Shum, Timothy M. Hospedales:
Editorial: Special Issue on Machine Vision with Deep Learning. Int. J. Comput. Vis. 128(4): 771-772 (2020) - [j26]Feng Liu, Tao Xiang, Timothy M. Hospedales, Wankou Yang, Changyin Sun:
Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool. IEEE Trans. Pattern Anal. Mach. Intell. 42(2): 460-474 (2020) - [j25]Zhong Ji, Biying Cui, Huihui Li, Yu-Gang Jiang, Tao Xiang, Timothy M. Hospedales, Yanwei Fu:
Deep Ranking for Image Zero-Shot Multi-Label Classification. IEEE Trans. Image Process. 29: 6549-6560 (2020) - [j24]Conghui Hu, Da Li, Yongxin Yang, Timothy M. Hospedales, Yi-Zhe Song:
Sketch-a-Segmenter: Sketch-Based Photo Segmenter Generation. IEEE Trans. Image Process. 29: 9470-9481 (2020) - [j23]Ayan Kumar Bhunia, Ayan Das, Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yulia Gryaditskaya, Yi-Zhe Song:
Pixelor: a competitive sketching AI agent. so you think you can sketch? ACM Trans. Graph. 39(6): 166:1-166:15 (2020) - [c110]Yu Zheng, Bowei Chen, Timothy M. Hospedales, Yongxin Yang:
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach. AAAI 2020: 1242-1249 - [c109]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Deep Domain-Adversarial Image Generation for Domain Generalisation. AAAI 2020: 13025-13032 - [c108]Shreyank N. Gowda, Panagiotis Eustratiadis, Timothy M. Hospedales, Laura Sevilla-Lara:
ALBA: Reinforcement Learning for Video Object Segmentation. BMVC 2020 - [c107]Mustafa Taha Koçyigit, Laura Sevilla-Lara, Timothy M. Hospedales, Hakan Bilen:
Unsupervised Batch Normalization. CVPR Workshops 2020: 3994-3999 - [c106]Jean Kossaifi, Antoine Toisoul, Adrian Bulat, Yannis Panagakis, Timothy M. Hospedales, Maja Pantic:
Factorized Higher-Order CNNs With an Application to Spatio-Temporal Emotion Estimation. CVPR 2020: 6059-6068 - [c105]Ayan Kumar Bhunia, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Sketch Less for More: On-the-Fly Fine-Grained Sketch-Based Image Retrieval. CVPR 2020: 9776-9785 - [c104]Kaiyue Pang, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Solving Mixed-Modal Jigsaw Puzzle for Fine-Grained Sketch-Based Image Retrieval. CVPR 2020: 10344-10352 - [c103]Juan-Manuel Pérez-Rúa, Xiatian Zhu, Timothy M. Hospedales, Tao Xiang:
Incremental Few-Shot Object Detection. CVPR 2020: 13843-13852 - [c102]Xiao Gong, Guosheng Hu, Timothy M. Hospedales, Yongxin Yang:
Adversarial Robustness of Open-Set Recognition: Face Recognition and Person Re-identification. ECCV Workshops (1) 2020: 135-151 - [c101]Da Li, Timothy M. Hospedales:
Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation. ECCV (16) 2020: 382-403 - [c100]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Learning to Generate Novel Domains for Domain Generalization. ECCV (16) 2020: 561-578 - [c99]Yonggang Li, Guosheng Hu, Yongtao Wang, Timothy M. Hospedales, Neil Martin Robertson, Yongxin Yang:
Differentiable Automatic Data Augmentation. ECCV (22) 2020: 580-595 - [c98]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Sequential Learning for Domain Generalization. ECCV Workshops (1) 2020: 603-619 - [c97]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
BézierSketch: A Generative Model for Scalable Vector Sketches. ECCV (26) 2020: 632-647 - [c96]Yu Zheng, Yunpeng Li, Qiuhua Xu, Timothy M. Hospedales, Yongxin Yang:
Index tracking with differentiate asset selection. ICAIF 2020: 12:1-12:8 - [c95]Yu Zheng, Timothy M. Hospedales, Yongxin Yang:
Diversity and Sparsity: A New Perspective on Index Tracking. ICASSP 2020: 1768-1772 - [c94]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep Clustering for Domain Adaptation. ICASSP 2020: 4247-4251 - [c93]Boyan Gao, Yongxin Yang, Henry Gouk, Timothy M. Hospedales:
Deep Clusteringwith Concrete K-Means. ICASSP 2020: 4252-4256 - [c92]Miguel Jaques, Michael Burke, Timothy M. Hospedales:
Physics-as-Inverse-Graphics: Unsupervised Physical Parameter Estimation from Video. ICLR 2020 - [c91]Marija Jegorova, Antti Ilari Karjalainen, Jose Vazquez, Timothy M. Hospedales:
Full-Scale Continuous Synthetic Sonar Data Generation with Markov Conditional Generative Adversarial Networks*. ICRA 2020: 3168-3174 - [c90]Xueting Zhang, Yuting Qiang, Flood Sung, Yongxin Yang, Timothy M. Hospedales:
RelationNet2: Deep Comparison Network for Few-Shot Learning. IJCNN 2020: 1-8 - [c89]Marija Jegorova, Joshua Smith, Michael N. Mistry, Timothy M. Hospedales:
Adversarial Generation of Informative Trajectories for Dynamics System Identification. IROS 2020: 7109-7115 - [c88]Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, Timothy M. Hospedales:
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods. NeurIPS 2020 - [i93]Henry Gouk, Timothy M. Hospedales, Massimiliano Pontil:
Distance-Based Regularisation of Deep Networks for Fine-Tuning. CoRR abs/2002.08253 (2020) - [i92]Peng Xu, Kun Liu, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma, Jun Guo, Yi-Zhe Song:
Fine-Grained Instance-Level Sketch-Based Video Retrieval. CoRR abs/2002.09461 (2020) - [i91]Ayan Kumar Bhunia, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
Sketch Less for More: On-the-Fly Fine-Grained Sketch Based Image Retrieval. CoRR abs/2002.10310 (2020) - [i90]Marija Jegorova, Antti Ilari Karjalainen, Jose Vazquez, Timothy M. Hospedales:
Unlimited Resolution Image Generation with R2D2-GANs. CoRR abs/2003.01063 (2020) - [i89]Marija Jegorova, Joshua Smith, Michael N. Mistry, Timothy M. Hospedales:
Adversarial Generation of Informative Trajectories for Dynamics System Identification. CoRR abs/2003.01190 (2020) - [i88]Yonggang Li, Guosheng Hu, Yongtao Wang, Timothy M. Hospedales, Neil Martin Robertson, Yongxing Yang:
DADA: Differentiable Automatic Data Augmentation. CoRR abs/2003.03780 (2020) - [i87]Juan-Manuel Pérez-Rúa, Xiatian Zhu, Timothy M. Hospedales, Tao Xiang:
Incremental Few-Shot Object Detection. CoRR abs/2003.04668 (2020) - [i86]Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, Timothy M. Hospedales:
Online Meta-Critic Learning for Off-Policy Actor-Critic Methods. CoRR abs/2003.05334 (2020) - [i85]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Deep Domain-Adversarial Image Generation for Domain Generalisation. CoRR abs/2003.06054 (2020) - [i84]Da Li, Yongxin Yang, Yi-Zhe Song, Timothy M. Hospedales:
Sequential Learning for Domain Generalization. CoRR abs/2004.01377 (2020) - [i83]Da Li, Timothy M. Hospedales:
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation. CoRR abs/2004.04398 (2020) - [i82]Timothy M. Hospedales, Antreas Antoniou, Paul Micaelli, Amos J. Storkey:
Meta-Learning in Neural Networks: A Survey. CoRR abs/2004.05439 (2020) - [i81]Xinwang Liu, En Zhu, Jiyuan Liu, Timothy M. Hospedales, Yang Wang, Meng Wang:
SimpleMKKM: Simple Multiple Kernel K-means. CoRR abs/2005.04975 (2020) - [i80]Stéphane Doncieux, Nicolas Bredèche, Leni K. Le Goff, Benoît Girard, Alexandre Coninx, Olivier Sigaud, Mehdi Khamassi, Natalia Díaz Rodríguez, David Filliat, Timothy M. Hospedales, A. E. Eiben, Richard J. Duro:
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics. CoRR abs/2005.06223 (2020) - [i79]Shreyank N. Gowda, Panagiotis Eustratiadis, Timothy M. Hospedales, Laura Sevilla-Lara:
ALBA : Reinforcement Learning for Video Object Segmentation. CoRR abs/2005.13039 (2020) - [i78]Lucas Deecke, Timothy M. Hospedales, Hakan Bilen:
Latent Domain Learning with Dynamic Residual Adapters. CoRR abs/2006.00996 (2020) - [i77]Miguel Jaques, Michael Burke, Timothy M. Hospedales:
NewtonianVAE: Proportional Control and Goal Identification from Pixels via Physical Latent Spaces. CoRR abs/2006.01959 (2020) - [i76]Carl Allen, Ivana Balazevic, Timothy M. Hospedales:
A Probabilistic Framework for Discriminative and Neuro-Symbolic Semi-Supervised Learning. CoRR abs/2006.05896 (2020) - [i75]Ondrej Bohdal, Yongxin Yang, Timothy M. Hospedales:
Flexible Dataset Distillation: Learn Labels Instead of Images. CoRR abs/2006.08572 (2020) - [i74]Linus Ericsson, Henry Gouk, Timothy M. Hospedales:
Don't Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights. CoRR abs/2006.12360 (2020) - [i73]Ayan Das, Yongxin Yang, Timothy M. Hospedales, Tao Xiang, Yi-Zhe Song:
BézierSketch: A generative model for scalable vector sketches. CoRR abs/2007.02190 (2020) - [i72]Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Learning the Prediction Distribution for Semi-Supervised Learning with Normalising Flows. CoRR abs/2007.02745 (2020) - [i71]Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, Tao Xiang:
Learning to Generate Novel Domains for Domain Generalization. CoRR abs/2007.03304 (2020) - [i70]Peng Xu, Yongye Huang, Tongtong Yuan, Tao Xiang, Timothy M. Hospedales, Yi-Zhe Song, Liang Wang:
On Learning Semantic Representations for Million-Scale Free-Hand Sketches. CoRR abs/2007.04101 (2020) - [i69]