News

[05.04.24] New paper accepted to L4DC 2024 - Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning

[16.02.24] New paper accepted to ICLR 2024 - Function-space Prameterization of Neural Networks for Sequential Learning

[03.10.23] Giving a talk on "(Function-space) Laplace approximation for Bayesian neural networks" to the NSF safe RL team.

[03.08.23] Presenting our work on “Neural Networks as Sparse Gaussian Processes for Sequential Learning” at the International Workshop of Intelligent Autonomous Learning Systems 2023.

[22.06.23] New paper accepted to the Duality Principles for Modern Machine Learning ICML 2023 Workshop - Sparse Function-Space Representation of Neural Networks.

[03.03.23] I’ve made a template for writing reproducible ML papers

[24.02.23] Camera-ready version of our AISTATS 2023 paper is now on my website - see here

[20.01.23] Visiting University of Cambridge 13th-14th February and presenting some of my research to ML@CL

[20.01.23] New paper accepted to AISTATS 2023 - “Mode-Constrained Model-Based Reinforcement Learning via Gaussian Processes”

[17.01.23] Co-lecturing on Aalto University’s Gaussian process course - “Sequential decision-making”

[16.11.22] Poster accepted at Finnish AI day - “Investigating BNN Dynamics Models for Model-Based RL”

[08.11.22] Guest lecture on Aalto University’s Reinforcement Learning course - “Model-based RL under uncertainty: the importance of knowing what you don’t know”

[04.07.22] Started as a postdoctoral researcher @ Aalto University

[23.06.22] Successfully defended my PhD