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2020 – today
- 2024
[i9]Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein:
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations. CoRR abs/2412.01441 (2024)- 2023
- [i8]Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang:
Vision-Language Models as a Source of Rewards. CoRR abs/2312.09187 (2023) - 2021
- [i7]Daniel Lenton, Fabio Pardo, Fabian Falck, Stephen James, Ronald Clark:
Ivy: Templated Deep Learning for Inter-Framework Portability. CoRR abs/2102.02886 (2021) - [i6]Vittorio La Barbera, Fabio Pardo, Yuval Tassa, Monica Daley, Christopher Richards, Petar Kormushev, John Hutchinson:
OstrichRL: A Musculoskeletal Ostrich Simulation to Study Bio-mechanical Locomotion. CoRR abs/2112.06061 (2021) - 2020
- [c4]Fabio Pardo, Vitaly Levdik, Petar Kormushev:
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks. AAAI 2020: 5355-5362 - [c3]Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel:
CoMic: Complementary Task Learning & Mimicry for Reusable Skills. ICML 2020: 4105-4115 - [i5]Fabio Pardo:
Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking. CoRR abs/2011.07537 (2020)
2010 – 2019
- 2018
- [c2]Arash Tavakoli, Fabio Pardo, Petar Kormushev:
Action Branching Architectures for Deep Reinforcement Learning. AAAI 2018: 4131-4138 - [c1]Fabio Pardo, Arash Tavakoli, Vitaly Levdik, Petar Kormushev:
Time Limits in Reinforcement Learning. ICML 2018: 4042-4051 - [i4]Fabio Pardo, Vitaly Levdik, Petar Kormushev:
Goal-oriented Trajectories for Efficient Exploration. CoRR abs/1807.02078 (2018) - [i3]Fabio Pardo, Vitaly Levdik, Petar Kormushev:
Q-map: a Convolutional Approach for Goal-Oriented Reinforcement Learning. CoRR abs/1810.02927 (2018) - 2017
- [i2]Arash Tavakoli, Fabio Pardo, Petar Kormushev:
Action Branching Architectures for Deep Reinforcement Learning. CoRR abs/1711.08946 (2017) - [i1]Fabio Pardo, Arash Tavakoli, Vitaly Levdik, Petar Kormushev:
Time Limits in Reinforcement Learning. CoRR abs/1712.00378 (2017)
Coauthor Index
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