Dino Oglic

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Thomas GärtnerTU Wien (Technical University of Vienna)Verified email at tuwien.ac.at
Dino SejdinovicProfessor of Statistical Machine Learning, University of AdelaideVerified email at adelaide.edu.au
Jean-Francois TonByteDance ResearchVerified email at bytedance.com
Zhu Li (Michael)University College LondonVerified email at ucl.ac.uk
David ButerezPhD student, University of CambridgeVerified email at cam.ac.uk
Jon Paul JanetAstraZeneca R&DVerified email at astrazeneca.com
Pietro LiòProfessor, University of CambridgeVerified email at cam.ac.uk
Zoran CvetkovicProfessor of Signal Processing, King's College LondonVerified email at byzanblue.net
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Steven KiddleAstraZenecaVerified email at astrazeneca.com
Steve RenalsUniversity of EdinburghVerified email at ed.ac.uk
Daniel PauratTelekom Deutschland TechnikVerified email at telekom.de
Peter BellUniversity of EdinburghVerified email at ed.ac.uk
Peter SollichProfessor Non-Equilibrium Statistical Physics, Inst. for Theor. Physics, University of GoettingenVerified email at uni-goettingen.de
Jonathan HirstProfessor of Computational Chemistry, University of NottinghamVerified email at nottingham.ac.uk
Neethu Mariam JoyKing's College LondonVerified email at ee.iitm.ac.in
Rebecca Croasdale-WoodAstraZenecaVerified email at astrazeneca.com
Bin YUProfessor of Statistics and EECS, UC BerkeleyVerified email at stat.berkeley.edu
Pietro SormanniRoyal Society University Research Fellow, Department of Chemistry, University of Cambridge.Verified email at cam.ac.uk
Tom DietheAstraZeneca; University of BristolVerified email at bristol.ac.uk

Dino Oglic

AstraZeneca Cambridge

Verified email at astrazeneca.com - Homepage

Machine Learning Kernel Methods Learning Theory Representation Learning Drug Design


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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	147	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	49	2021
Graph Neural Networks with Adaptive Readouts D Buterez, JP Janet, SJ Kiddle, D Oglic, P Liò Advances in Neural Information Processing Systems, 2022	46	2022
Nyström Method with Kernel K-means++ Samples as Landmarks D Oglic, T Gaertner Proceedings of the 34th International Conference on Machine Learning, 2017	46	2017
Learning in reproducing kernel Kreı̆n spaces D Oglic, T Gärtner Proceedings of the 35th International Conference on Machine Learning, 2018	36	2018
Active Search for Computer‐Aided Drug Design D Oglic, SA Oatley, SJF Macdonald, T Mcinally, R Garnett, JD Hirst, ... Molecular Informatics, 2018	30	2018
Scalable Learning in Reproducing Kernel Krein Spaces D Oglic, T Gärtner Proceedings of the 36th International Conference on Machine Learning, 4912-4921, 2019	25	2019
Greedy Feature Construction D Oglic, T Gaertner Advances in Neural Information Processing Systems, 2016	16	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
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	8	2024
Supervised PCA for interactive data analysis D Paurat, D Oglic, T Gärtner 2nd NIPS Workshop on Spectral Learning, 2013	8	2013
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	7	2021
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
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	6	2023
Constructive Approximation and Learning by Greedy Algorithms D Oglic Universitäts-und Landesbibliothek Bonn, 2018	3	2018
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	2	2022
Learning to Construct Novel Structures D Oglic, R Garnett, T Gärtner NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning …, 2014	2	2014
p-IgGen: A Paired Antibody Generative Language Model OM Turnbull, D Oglic, R Croasdale-Wood, C Deane ICLR Workshop on Generative and Experimental Perspectives for Biomolecular …, 2024	1	2024

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