Full Program

Breakfast

Lecture 2: Learning factored transition models for planning in complex hybrid spaces

Lecture 2

Coffee Break

Lecture 2: Meta-learning

Lecture 2: Conditional GANs and Data Prediction

Lunch

Lecture 3: Integrating Domain-Knowledge into Deep Learning

Lecture 1: The Principle of Least Cognitive Action

Coffee Break

Lecture 2: Model-based reinforcement learning II

Lecture 3: AlphaZero: A general model-based planning reinforcement learning algorithm for board games

Dinner

Breakfast

Lecture 3

Lecture 3: Learning to speed up planning in complex hybrid spaces

Coffee Break

Lecture 2: Quasi-Periodic Temporal Environments

Lecture 3: AutoML and meta-learning for neural networks

Lunch

Lecture 1: Latest advances in enhancing Interpretability in Data Science via means of Mathematical Optimization (Part 1)

Lecture 3: GANs for Domain Translation

Coffee Break

Building Iride: how to mix deep learning and Ontologies techiniques to understand language

Flash-talk: tell me about yourself in five minutes

Dinner

Breakfast

Lecture 1: The Information Theory of Deep Learning: Towards Interpretable Deep Neural Networks - Rethinking Computational Learning theory

Lecture 1: Advanced topics: Graph Neural Networks

Coffee Break

Lecture 1: KNIME training session 1

Lecture 2: The Information Theory of Deep Learning: Towards Interpretable Deep Neural Networks - The role Stochastic Gradient Descent in achieving the Information Bottleneck optimal bound

Lunch

Lecture 2: Latest advances in enhancing Interpretability in Data Science via means of Mathematical Optimization (Part 2)

Lecture 3: Developmental Visual Agents

Coffee Break

Lecture 2: KNIME training session 2

Lecture 3: Data-intensive Knowledge Discovery from Brain Imaging of Alzheimer’s Disease Patients

Dinner

Breakfast

Lecture 2: Reinforcement and Imitation Learning at Scale: AlphaStar and Beyond

Lecture 3: The Information Theory of Deep Learning: Towards Interpretable Deep Neural Networks - The computational benefits of the hidden layers and the role of symmetry for the interpretability of the layers

Coffee Break

Lecture 3: Representation Learning With Generative Models

Lecture 3: Latest advances in enhancing Interpretability in Data Science via means of Mathematical Optimization (part 3)

Lunch

Social Tour of Siena & Dinner in Contrada