1 code implementation • 21 Oct 2022 • Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi-Kahou
Learning world models from their sensory inputs enables agents to plan for actions by imagining their future outcomes.
no code implementations • NeurIPS 2021 • Nasim Rahaman, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, Bernhard Schölkopf
Modern neural network architectures can leverage large amounts of data to generalize well within the training distribution.
no code implementations • 14 Oct 2020 • Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wüthrich, Bernhard Schölkopf
This \emph{meta-representation}, which is computed from a few observed examples of the underlying function, is learned jointly with the predictive model.
no code implementations • 28 Sep 2020 • Muhammad Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf
Few-shot-learning seeks to find models that are capable of fast-adaptation to novel tasks which are not encountered during training.
2 code implementations • 8 Aug 2020 • Manuel Wüthrich, Felix Widmaier, Felix Grimminger, Joel Akpo, Shruti Joshi, Vaibhav Agrawal, Bilal Hammoud, Majid Khadiv, Miroslav Bogdanovic, Vincent Berenz, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Bernhard Schölkopf, Stefan Bauer
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade.
no code implementations • 17 Jul 2018 • Homanga Bharadhwaj, Shruti Joshi
Recommendation systems are an integral part of Artificial Intelligence (AI) and have become increasingly important in the growing age of commercialization in AI.