Dino Oglic

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Thomas GärtnerTU Wien (Technical University of Vienna)Dirección de correo verificada de tuwien.ac.at
Dino SejdinovicProfessor of Statistical Machine Learning, University of AdelaideDirección de correo verificada de adelaide.edu.au
Jean-Francois TonByteDance ResearchDirección de correo verificada de bytedance.com
Zhu Li (Michael)University College LondonDirección de correo verificada de ucl.ac.uk
Zoran CvetkovicProfessor of Signal Processing, King's College LondonDirección de correo verificada de byzanblue.net
Roman GarnettWashington University in St. LouisDirección de correo verificada de wustl.edu
David ButerezPhD student, University of CambridgeDirección de correo verificada de cam.ac.uk
Jon Paul JanetAstraZeneca R&DDirección de correo verificada de astrazeneca.com
Pietro LiòProfessor, University of CambridgeDirección de correo verificada de cam.ac.uk
Steven KiddleAstraZenecaDirección de correo verificada de astrazeneca.com
Steve RenalsUniversity of EdinburghDirección de correo verificada de ed.ac.uk
Daniel PauratTelekom Deutschland TechnikDirección de correo verificada de telekom.de
Peter BellUniversity of EdinburghDirección de correo verificada de ed.ac.uk
Peter SollichProfessor Non-Equilibrium Statistical Physics, Inst. for Theor. Physics, University of GoettingenDirección de correo verificada de uni-goettingen.de
Jonathan HirstProfessor of Computational Chemistry, University of NottinghamDirección de correo verificada de nottingham.ac.uk
Neethu Mariam JoyKing's College LondonDirección de correo verificada de ee.iitm.ac.in
Bin YUProfessor of Statistics and EECS, UC BerkeleyDirección de correo verificada de stat.berkeley.edu
Pietro SormanniRoyal Society University Research Fellow, Department of Chemistry, University of Cambridge.Dirección de correo verificada de cam.ac.uk
Michael J. CurtisKing's College LondonDirección de correo verificada de kcl.ac.uk
HK Lam, Hak Keung LamDepartment of Engineering, King's College LondonDirección de correo verificada de kcl.ac.uk

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Dino Oglic

AstraZeneca Cambridge

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Machine Learning Kernel Methods Learning Theory Representation Learning Drug Design


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Towards A Unified Analysis of Random Fourier Features Z Li, JF Ton, D Oglic, D Sejdinovic Proceedings of the 36th International Conference on Machine Learning, PMLR, 2019	135	2019
Towards a Unified Analysis of Random Fourier Features Z Li, JF Ton, D Oglic, D Sejdinovic Journal of Machine Learning Research 22 (108), 1-51, 2021	43	2021
Nyström Method with Kernel K-means++ Samples as Landmarks D Oglic, T Gaertner Proceedings of the 34th International Conference on Machine Learning, 2017	43	2017
Learning in reproducing kernel Kreı̆n spaces D Oglic, T Gärtner Proceedings of the 35th International Conference on Machine Learning, 2018	34	2018
Active Search for Computer‐Aided Drug Design D Oglic, SA Oatley, SJF Macdonald, T Mcinally, R Garnett, JD Hirst, ... Molecular Informatics, 2018	29	2018
Graph Neural Networks with Adaptive Readouts D Buterez, JP Janet, SJ Kiddle, D Oglic, P Liò Advances in Neural Information Processing Systems, 2022	28	2022
Scalable Learning in Reproducing Kernel Krein Spaces D Oglic, T Gärtner Proceedings of the 36th International Conference on Machine Learning, 4912-4921, 2019	22	2019
Greedy Feature Construction D Oglic, T Gaertner Advances in Neural Information Processing Systems, 2016	15	2016
A Deep 2D Convolutional Network for Waveform-based Speech Recognition D Oglic, Z Cvetkovic, P Bell, S Renals The 21st Annual Conference of International Speech Communication Association …, 2020	13	2020
Interactive Knowledge-Based Kernel PCA⋆ D Oglic, D Paurat, T Gärtner Proceedings of Machine Learning and Knowledge Discovery in Databases …, 2014	13	2014
Active search in intensionally specified structured spaces D Oglic, R Garnett, T Gärtner Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence …, 2017	9	2017
Supervised PCA for interactive data analysis D Paurat, D Oglic, T Gärtner 2nd NIPS Workshop on Spectral Learning, 2013	8	2013
Deep Scattering Power Spectrum Features for Robust Speech Recognition NM Joy, D Oglic, Z Cvetkovic, P Bell, S Renals The 21st Annual Conference of International Speech Communication Association …, 2020	7	2020
Learning Waveform-Based Acoustic Models Using Deep Variational Convolutional Neural Networks D Oglic, Z Cvetkovic, P Sollich IEEE/ACM Transactions on Audio, Speech, and Language Processing 29, 2850-2863, 2021	6	2021
Modelling local and general quantum mechanical properties with attention-based pooling D Buterez, JP Janet, SJ Kiddle, D Oglic, P Liò Communications Chemistry 6, 2023	4	2023
Constructive Approximation and Learning by Greedy Algorithms D Oglic Universitäts-und Landesbibliothek Bonn, 2018	3	2018
Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting D Buterez, JP Janet, S Kiddle, D Oglic, P Liò Nature Communications 15, 2024	2	2024
Learning to Construct Novel Structures D Oglic, R Garnett, T Gärtner NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning …, 2014	2	2014
Towards Robust Waveform-Based Acoustic Models D Oglic, Z Cvetkovic, P Sollich, S Renals, B Yu IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 1977-1992, 2022	1	2022
A Hybrid GCN-LSTM Model for Ventricular Arrhythmia Classification Based on ECG Pattern Similarity Q Lin, D Oglic, HK Lam, M Curtis, Z Cvetkovic International Conference of the IEEE Engineering in Medicine and Biology …, 2024		2024

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