Kai Arulkumaran
Cited by
Cited by
A Brief Survey of Deep Reinforcement Learning
K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath
IEEE Signal Processing Magazine 34 (6), 26-38, 2017
Generative Adversarial Networks: An Overview
A Creswell, T White, V Dumoulin, K Arulkumaran, B Sengupta, ...
IEEE Signal Processing Magazine 35 (1), 53-65, 2018
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders
N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ...
arXiv preprint arXiv:1611.02648, 2016
AlphaStar: An Evolutionary Computation Perspective
K Arulkumaran, A Cully, J Togelius
Genetic and Evolutionary Computation Conference Companion, 314-315, 2019
Towards Deep Symbolic Reinforcement Learning
M Garnelo, K Arulkumaran, M Shanahan
Workshop on Deep Reinforcement Learning, Neural Information Processing Systems, 2016
Adaptive Neural Trees
R Tanno, K Arulkumaran, DC Alexander, A Criminisi, A Nori
International Conference on Machine Learning, 2019
On Denoising Autoencoders Trained to Minimise Binary Cross-entropy
A Creswell, K Arulkumaran, AA Bharath
arXiv preprint arXiv:1708.08487, 2017
The Societal Implications of Deep Reinforcement Learning
J Whittlestone, K Arulkumaran, M Crosby
Journal of Artificial Intelligence Research 70, 1003-1030, 2021
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation
T Dai, K Arulkumaran, T Gerbert, S Tukra, F Behbahani, AA Bharath
Neurocomputing 493, 143-165, 2022
Image Synthesis with a Convolutional Capsule Generative Adversarial Network
C Bass, T Dai, B Billot, K Arulkumaran, A Creswell, C Clopath, V De Paola, ...
International Conference on Medical Imaging with Deep Learning 102, 38-61, 2019
Classifying Options for Deep Reinforcement Learning
K Arulkumaran, N Dilokthanakul, M Shanahan, AA Bharath
Workshop on Deep Reinforcement Learning: Frontiers and Challenges …, 2016
On the Link Between Conscious Function and General Intelligence in Humans and Machines
A Juliani, K Arulkumaran, S Sasai, R Kanai
Transactions on Machine Learning Research, 2022
BETH Dataset: Real Cybersecurity Data for Anomaly Detection Research
K Highnam, K Arulkumaran, Z Hanif, NR Jennings
Conference on Applied Machine Learning for Information Security, 2021
Deep Reinforcement Learning for Subpixel Neural Tracking
T Dai, M Dubois, K Arulkumaran, J Campbell, C Bass, B Billot, F Uslu, ...
International Conference on Medical Imaging with Deep Learning 102, 110-131, 2019
Variational Inference for Data-Efficient Model Learning in POMDPs
S Tschiatschek, K Arulkumaran, J Stühmer, K Hofmann
arXiv preprint arXiv:1805.09281, 2018
Improving Sampling from Generative Autoencoders with Markov Chains
K Arulkumaran, A Creswell, AA Bharath
arXiv preprint arXiv:1610.09296, 2016
EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis
K Pan, G Hurault, K Arulkumaran, H Williams, RJ Tanaka
International Workshop on Machine Learning in Medical Imaging, 2020
Privileged Information Dropout in Reinforcement Learning
PA Kamienny, K Arulkumaran, F Behbahani, W Böhmer, S Whiteson
Beyond “Tabula Rasa” in Reinforcement Learning Workshop, International …, 2020
Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay
T Dai, H Liu, K Arulkumaran, G Ren, AA Bharath
Pacific Rim International Conference on Artificial Intelligence, 2021
An Analysis of Emergency Tracheal Intubations in Critically Ill Patients by Critical Care Trainees
N Arulkumaran, CS McLaren, K Arulkumaran, BJ Philips, M Cecconi
Journal of the Intensive Care Society 19 (3), 180-187, 2018
The system can't perform the operation now. Try again later.
Articles 1–20