Dino Oglic

According to our database, Dino Oglic authored at least 19 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Active learning for affinity prediction of antibodies.

Alexandra Gessner, Sebastian W. Ober, Owen Vickery, Dino Oglic, Talip Uçar

CoRR, 2024

Masked Attention is All You Need for Graphs.

David Buterez, Jon Paul Janet, Dino Oglic, Pietro Lio

CoRR, 2024

Improving Antibody Humanness Prediction using Patent Data.

Talip Ucar, Aubin Ramon, Dino Oglic, Rebecca Croasdale-Wood, Tom Diethe, Pietro Sormanni

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022

Towards Robust Waveform-Based Acoustic Models.

Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu

IEEE ACM Trans. Audio Speech Lang. Process., 2022

Graph Neural Networks with Adaptive Readouts.

David Buterez, Jon Paul Janet, Steven J. Kiddle, Dino Oglic, Pietro Liò

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Learning Waveform-Based Acoustic Models Using Deep Variational Convolutional Neural Networks.

Dino Oglic, Zoran Cvetkovic, Peter Sollich

IEEE ACM Trans. Audio Speech Lang. Process., 2021

Towards a Unified Analysis of Random Fourier Features.

Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic

J. Mach. Learn. Res., 2021

2020

A Deep 2D Convolutional Network for Waveform-Based Speech Recognition.

Dino Oglic, Zoran Cvetkovic, Peter Bell, Steve Renals

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

Deep Scattering Power Spectrum Features for Robust Speech Recognition.

Neethu M. Joy, Dino Oglic, Zoran Cvetkovic, Peter Bell, Steve Renals

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

2019

Parzen Filters for Spectral Decomposition of Signals.

Dino Oglic, Zoran Cvetkovic, Peter Sollich

CoRR, 2019

Scalable Learning in Reproducing Kernel Krein Spaces.

Dino Oglic, Thomas Gärtner

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Constructive Approximation and Learning by Greedy Algorithms.

Dino Oglic

PhD thesis, 2018

Large Scale Learning with Kreĭn Kernels.

Dino Oglic, Thomas Gärtner

CoRR, 2018

A Unified Analysis of Random Fourier Features.

Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic

CoRR, 2018

Learning in Reproducing Kernel Krein Spaces.

Dino Oglic, Thomas Gärtner

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Nyström Method with Kernel K-means++ Samples as Landmarks.

Dino Oglic, Thomas Gärtner

Proceedings of the 34th International Conference on Machine Learning, 2017

Active Search in Intensionally Specified Structured Spaces.

Dino Oglic, Roman Garnett, Thomas Gärtner

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Greedy Feature Construction.

Dino Oglic, Thomas Gärtner

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2014

Interactive Knowledge-Based Kernel PCA.

Dino Oglic, Daniel Paurat, Thomas Gärtner

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014