6 citations · 6 across the 1 of their papers we have counts for
4 papers
Ivy: Templated Deep Learning for Inter-Framework Portability
Daniel Lenton, Fabio Pardo, Fabian Falck +2
We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks. Ivy unifies the core functions of these frameworks to exhibit consistent call sig…
Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking
Fabio Pardo
Deep reinforcement learning has been one of the fastest growing fields of machine learning over the past years and numerous libraries have been open sourced to support research. Ho…
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks
Fabio Pardo, Vitaly Levdik, Petar Kormushev
Being able to reach any desired location in the environment can be a valuable asset for an agent. Learning a policy to navigate between all pairs of states individually is often no…
Goal-oriented Trajectories for Efficient Exploration
Fabio Pardo, Vitaly Levdik, Petar Kormushev
Exploration is a difficult challenge in reinforcement learning and even recent state-of-the art curiosity-based methods rely on the simple epsilon-greedy strategy to generate novel…