Yannis Assael
Yannis Assael
Research Scientist, DeepMind
Verified email at google.com - Homepage
TitleCited byYear
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
3412016
LipNet: end-to-end sentence-level lipreading
YM Assael, B Shillingford, S Whiteson, N de Freitas
GPU Technology Conference 2017, 2016
1782016
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
632016
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
352011
Multi-objective deep reinforcement learning
H Mossalam, YM Assael, DM Roijers, S Whiteson
NIPS Deep Reinforcement Learning Workshop, 2016
302016
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
29*2019
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
262017
Large-scale visual speech recognition
B Shillingford, Y Assael, MW Hoffman, T Paine, C Hughes, U Prabhu, ...
Interspeech, 4135-4139, 2019
222019
Heteroscedastic treed bayesian optimisation
JAM Assael, Z Wang, B Shahriari, N de Freitas
NIPS Workshop on Bayesian Optimization, 2014
142014
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
122018
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
102015
Data-efficient learning of feedback policies from image pixels using deep dynamical models
JAM Assael, N Wahlström, TB Schön, MP Deisenroth
NIPS Deep Reinforcement Learning Workshop, 2015
102015
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
92015
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
72010
String matching on hybrid parallel architectures, an approach using MPI and NVIDIA CUDA
JAM Assael, K Margaritis
http://www.yannisassael.com/publications/assael_uom_dissertation.pdf, 2013
12013
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
2019
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
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
2017
From pixels to torques: policy learning using deep dynamical convolutional networks
JAM Assael, MP Deisenroth
Imperial College London, 2015
2015
Study and application of discomfort indices in Greece
MJ Assael, KE Kakosimos, A Alexandridis, JAM Assael
7th National Scientific Chemical Engineering Conference, Patra, Proceedings, 2009
2009
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Articles 1–20