Online Course
Non-Markov Decision Processes and Reinforcement Learning
We present non-Markov decision processes, where rewards and dynamics can depend on the history of events. This is contrast with Markov Decision Processes, where the dependency is limited to the last state and action.
Article/Books/eBooks
Cooperating with machines
Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go).
Article/Books/eBooks
Should we fear the robot revolution? (The correct answer is yes)
Advances in artificial intelligence and robotics may be leading to a new industrial revolution. This paper presents a model with the minimum necessary features to analyze the implications for inequality and output.
Article/Books/eBooks
An Open Dataset of Synthetic Speech
This paper introduces a multilingual, multispeaker dataset composed of synthetic and natural speech, designed to foster research and benchmarking in synthetic speech detection.
Article/Books/eBooks
Advancing Audio Phylogeny: A Neural Network Approach for Transformation Detection
In this study we propose a novel approach to audio phylogeny, i.e. the detection of relationships and transformations within a set of near-duplicate audio items, by leveraging a deep neural network for efficiency and extensibility.
Software resources
gnntf: A Flexible Deep Graph Neural Network Framework
This repository provides a framework for easy experimentation with Graph Neural Network (GNN) architectures by separating them from predictive components.