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ADSAI 2022 Contributed Talks

The following contributors were selected to present short talks at the conference.

Multi-Means Gaussian Processes: A novel probabilistic framework for multi-correlated longitudinal data
Arthur Leroy, Research Associate in Computer Science, The University of Sheffield
Co-authors: Mauricio A Álvarez, The University of Manchester

Scalable Bigraphical Lasso: Two-way Sparse Network Inference for Count Data
Sijia Li, PhD candidate, University of Leeds
Co-authors: Martín López-García, Neil Lawrence and Luisa Cutillo

Benchmarking Safe Optimization Algorithms: Methodology, Software and Validation
Youngmin Kim, PhD Candidate, The University of Manchester
Co-authors: Richard Allmendinger and Manuel López-Ibáñez

Large-Scale Predictive Models in Education – New Data and Improved Accuracy
Tom Quilter, Senior Engineer, Pinpoint Learning
Co-authors: Richard Turner, Anastasija Ilic and Karen Poon

Approximate Bayesian Computation with Domain Expert in the Loop
Louis Filstroff, Postdoctoral Researcher, Aalto University
Co-authors: Ayush Bharti and Samuel Kaski

Towards Virtual Laboratories: AI Assistance in Experimentation
Christopher McGreavy, Postdoctoral Researcher, Aalto University
Co-authors: Carlos Sevilla-Salcedo, Arto Klami and Samuel Kaski

American Sign Language acquisition via Imitation Learning
Federico Tavella, PhD Candidate, The University of Manchester
Co-authors: Aphrodite Galata and Angelo Cangelosi

HMM-based clustering of multimorbidity trajectories
Benediktas Valys, PhD Candidate, University of Sheffield
Co-authors: Ilaria Bellantuono, Amaia Calderon Larrañaga, Alessandra Marengoni, Davide Liborio Vetrano, Mauricio Álvarez and Mari-Cruz Villa-Uriol

Improving Neural Networks for Genotype-Phenotype Prediction Using Published Summary Statistics
Tianyu Cui, PhD Candidate, Aalto University
Co-authors: Khaoula El Mekkaoui, Aki Havulinna, Pekka Marttinen and Samuel Kaski

Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional Autoencoder
Matthew Lyon, PhD Candidate, The University of Manchester
Co-authors: Paul Armitage and Mauricio Alvarez