Learning to communicate with deep multi-agent reinforcement learning JN Foerster, YM Assael, N de Freitas, S Whiteson Advances in Neural Information Processing Systems, 2145-2153, 2016 | 690 | 2016 |
LipNet: end-to-end sentence-level lipreading YM Assael, B Shillingford, S Whiteson, N De Freitas GPU Technology Conference, 2017 | 299* | 2017 |
Learning to communicate to solve riddles with deep distributed recurrent Q-networks JN Foerster, YM Assael, N de Freitas, S Whiteson International Joint Conferences on Artificial Intelligence Workshop, 2016 | 98 | 2016 |
Large-scale visual speech recognition B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ... INTERSPEECH, 4135-4139, 2019 | 54 | 2019 |
Sample efficient adaptive text-to-speech Y Chen, Y Assael, B Shillingford, D Budden, S Reed, H Zen, Q Wang, ... International Conference on Learning Representations, 2019 | 53* | 2019 |
Multi-objective deep reinforcement learning H Mossalam, YM Assael, DM Roijers, S Whiteson Advances in Neural Information Processing Systems Deep Reinforcement …, 2016 | 53 | 2016 |
Cortical microcircuits as gated-recurrent neural networks R Ponte Costa, Y Assael, B Shillingford, N de Freitas, T Vogels Advances in Neural Information Processing Systems, 272-283, 2017 | 47* | 2017 |
Correlation of the thermal conductivity of normal and parahydrogen from the triple point to 1000 K and up to 100 MPa MJ Assael, YM Assael, ML Huber, RA Perkins, Y Takata Journal of Physical and Chemical Reference Data 40 (3), 033101-033101-13, 2011 | 37 | 2011 |
Using deep Q-learning to understand the tax evasion behavior of risk-averse firms ND Goumagias, D Hristu-Varsakelis, YM Assael Expert Systems with Applications 101, 258-270, 2018 | 22 | 2018 |
Heteroscedastic treed bayesian optimisation JAM Assael, Z Wang, B Shahriari, N de Freitas Advances in Neural Information Processing Systems Workshop on Bayesian …, 2014 | 19* | 2014 |
A novel portable absolute transient hot-wire instrument for the measurement of the thermal conductivity of solids MJ Assael, KD Antoniadis, IN Metaxa, SK Mylona, JAM Assael, J Wu, ... International Journal of Thermophysics 36 (10-11), 3083-3105, 2015 | 17 | 2015 |
Recurrent neural network transducer for audio-visual speech recognition T Makino, H Liao, Y Assael, B Shillingford, B Garcia, O Braga, O Siohan IEEE Automatic Speech Recognition and Understanding Workshop, 2019 | 11 | 2019 |
A hybrid parallel implementation of the Aho-Corasick and Wu-Manber algorithms using NVIDIA CUDA and MPI evaluated on a biological sequence database CS Kouzinopoulos, JAM Assael, TK Pyrgiotis, KG Margaritis International Journal on Artificial Intelligence Tools 24 (1), 1540001, 2015 | 10 | 2015 |
Restoring ancient text using deep learning: a case study on Greek epigraphy Y Assael, T Sommerschield, J Prag Empirical Methods in Natural Language Processing, 6369-6376, 2019 | 9 | 2019 |
Data-efficient learning of feedback policies from image pixels using deep dynamical models JAM Assael, N Wahlström, TB Schön, MP Deisenroth Advances in Neural Information Processing Systems Deep Reinforcement …, 2015 | 8 | 2015 |
Applying thermal comfort indices to investigate aspects of the climate change in Greece MJ Assael, KE Kakosimos, KD Antoniadis, JAM Assael International Review of Chemical Engineering 2, 204-209, 2010 | 8 | 2010 |
Speech bandwidth extension with WaveNet A Gupta, B Shillingford, Y Assael, TC Walters IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2019 | 7 | 2019 |
From analog timers to the era of machine learning: The case of the transient hot-wire technique YM Assael, KD Antoniadis, MJ Assael AIP Conference Proceedings 1866 (1), 020001, 2017 | 1 | 2017 |
From pixels to torques: policy learning using deep dynamical convolutional networks JAM Assael, MP Deisenroth Imperial College London, 2015 | 1 | 2015 |
String matching on hybrid parallel architectures, an approach using MPI and NVIDIA CUDA JAM Assael, K Margaritis http://www.assael.gr/publications/assael_uom_dissertation.pdf, 2013 | 1 | 2013 |