Timezone: »
Author Information
Wessel Bruinsma (University of Cambridge and Invenia Labs)
Eric Perim Martins (Invenia Labs)
William Tebbutt (University of Cambridge)
Scott Hosking (British Antarctic Survey)
Arno Solin (Aalto University)

Dr. Arno Solin is Assistant Professor in Machine Learning at the Department of Computer Science, Aalto University, Finland, and Adjunct Professor (Docent) at Tampere University, Finland. His research focuses on probabilistic models combining statistical machine learning and signal processing with applications in sensor fusion, robotics, computer vision, and online decision making. He has published around 50 peer-reviewed articles and one book. Previously, he has been a visiting researcher at Uppsala University (2019), University of Cambridge (2017-2018), and University of Sheffield (2014), and worked as a Team Lead in a tech startup. Prof. Solin is the winner of several prizes, hackathons, and modelling competitions, including the Schizophrenia Classification Challenge on Kaggle and the ISIF Jean-Pierre Le Cadre Best Paper Award. Homepage: http://arno.solin.fi
Richard E Turner (University of Cambridge)
Richard Turner holds a Lectureship (equivalent to US Assistant Professor) in Computer Vision and Machine Learning in the Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, UK. He is a Fellow of Christ's College Cambridge. Previously, he held an EPSRC Postdoctoral research fellowship which he spent at both the University of Cambridge and the Laboratory for Computational Vision, NYU, USA. He has a PhD degree in Computational Neuroscience and Machine Learning from the Gatsby Computational Neuroscience Unit, UCL, UK and a M.Sci. degree in Natural Sciences (specialism Physics) from the University of Cambridge, UK. His research interests include machine learning, signal processing and developing probabilistic models of perception.
More from the Same Authors
-
2021 : Attacking Few-Shot Classifiers with Adversarial Support Poisoning »
Elre Oldewage · John Bronskill · Richard E Turner -
2023 : Beyond Intuition, a Framework for Applying GPs to Real-World Data »
Kenza Tazi · Jihao Andreas Lin · ST John · Hong Ge · Richard E Turner · Ross Viljoen · Alex Gardner -
2023 : Sparse Function-space Representation of Neural Networks »
Aidan Scannell · Riccardo Mereu · Paul Chang · Ella Tamir · Joni Pajarinen · Arno Solin -
2023 : Memory Maps to Understand Models »
Dharmesh Tailor · Paul Chang · Siddharth Swaroop · Eric Nalisnick · Arno Solin · Khan Emtiyaz -
2023 : Modeling Accurate Long Rollouts with Temporal Neural PDE Solvers »
Phillip Lippe · Bastiaan Veeling · Paris Perdikaris · Richard E Turner · Johannes Brandstetter -
2023 Oral: Memory-Based Dual Gaussian Processes for Sequential Learning »
Paul Chang · Prakhar Verma · ST John · Arno Solin · Khan Emtiyaz -
2023 Poster: Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models »
Rui Li · ST John · Arno Solin -
2023 Poster: Memory-Based Dual Gaussian Processes for Sequential Learning »
Paul Chang · Prakhar Verma · ST John · Arno Solin · Khan Emtiyaz -
2020 Poster: State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes »
William Wilkinson · Paul Chang · Michael Andersen · Arno Solin -
2020 Poster: TaskNorm: Rethinking Batch Normalization for Meta-Learning »
John Bronskill · Jonathan Gordon · James Requeima · Sebastian Nowozin · Richard E Turner -
2020 Tutorial: Machine Learning with Signal Processing »
Arno Solin -
2019 Poster: End-to-End Probabilistic Inference for Nonstationary Audio Analysis »
William Wilkinson · Michael Riis Andersen · Joshua D. Reiss · Dan Stowell · Arno Solin -
2019 Oral: End-to-End Probabilistic Inference for Nonstationary Audio Analysis »
William Wilkinson · Michael Riis Andersen · Joshua D. Reiss · Dan Stowell · Arno Solin -
2018 Poster: State Space Gaussian Processes with Non-Gaussian Likelihood »
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy -
2018 Oral: State Space Gaussian Processes with Non-Gaussian Likelihood »
Hannes Nickisch · Arno Solin · Alexander Grigorevskiy -
2018 Poster: The Mirage of Action-Dependent Baselines in Reinforcement Learning »
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine -
2018 Oral: The Mirage of Action-Dependent Baselines in Reinforcement Learning »
George Tucker · Surya Bhupatiraju · Shixiang Gu · Richard E Turner · Zoubin Ghahramani · Sergey Levine -
2018 Poster: Structured Evolution with Compact Architectures for Scalable Policy Optimization »
Krzysztof Choromanski · Mark Rowland · Vikas Sindhwani · Richard E Turner · Adrian Weller -
2018 Oral: Structured Evolution with Compact Architectures for Scalable Policy Optimization »
Krzysztof Choromanski · Mark Rowland · Vikas Sindhwani · Richard E Turner · Adrian Weller -
2017 Poster: Magnetic Hamiltonian Monte Carlo »
Nilesh Tripuraneni · Mark Rowland · Zoubin Ghahramani · Richard E Turner -
2017 Talk: Magnetic Hamiltonian Monte Carlo »
Nilesh Tripuraneni · Mark Rowland · Zoubin Ghahramani · Richard E Turner -
2017 Poster: Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control »
Natasha Jaques · Shixiang Gu · Dzmitry Bahdanau · Jose Miguel Hernandez-Lobato · Richard E Turner · Douglas Eck -
2017 Talk: Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control »
Natasha Jaques · Shixiang Gu · Dzmitry Bahdanau · Jose Miguel Hernandez-Lobato · Richard E Turner · Douglas Eck