08:00–08:15

Opening

08:15–09:15

Keynote 1: Michael Unser - Splines and Machine Learning: From classical RKHS methods to deep neural networks

09:15–09:30

Break: Aalto University Campus Introduction

09:30–11:00

Tutorial: Aki Vehtari - Stan and probabilistic programming

11:00–12:00

Break

12:00–14:00

Lecture Session 1: Neural Networks and Applications 1

14:00–15:00

Poster Session 1: Applications in Multimedia and Biomedical Signal Processing

08:00–09:00

Keynote 2: Ole Winther - Latent variable models from independent components to VAEs and flows

09:00–09:15

Break: Introduction to the Espoo and Helsinki Area

09:15–11:15

Lecture Session 2: Acoustic Signal Processing using Machine Learning

11:15–12:15

Break

12:15–14:15

Lecture Session 3: Bayesian Learning and Modelling

14:15–15:15

Poster Session 2: Neural Networks and Applications 2

08:00–09:00

Keynote 3: Mihaela van der Schaar - Machine learning: Changing the future of healthcare

09:00–09:15

Break: Aalto University Campus Introduction

09:15–11:15

Lecture Session 4: Deep Learning for Inverse Problems

11:15–12:15

Break: Ida Elina Music

12:15–14:15

Lecture Session 5: Learning Theory, Modeling, and Graphical Models

14:15–15:15

Poster Session 3: Learning Theory and Bayesian Modeling

08:00–09:00

Keynote 4: Razvan Pascanu - Improving learning efficiency for deep neural networks

09:00–09:15

Break: Aalto University Campus Introduction

09:15–11:15

Lecture Session 6: Robust and High-Dimensional Statistical Learning for Signal Processing Applications

11:15–12:15

Break: Ida Elina Music

12:15–14:15

Lecture Session 7: Applications in Audio Processing and Bioinformatics

14:15–15:15

Poster Session 4: Learning: Theory, Modelling and Applications

15:15–16:00

Paper Awards and Closing Ceremony