default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKai Arulkumaran
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
Books and Theses
- 2020
[b1]Kai Arulkumaran:
Sample efficiency, transfer learning and interpretability for deep reinforcement learning. Imperial College London, UK, 2020
Journal Articles
- 2024
- [j9]Rousslan Fernand Julien Dossa, Kai Arulkumaran, Arthur Juliani, Shuntaro Sasai, Ryota Kanai:
Design and evaluation of a global workspace agent embodied in a realistic multimodal environment. Frontiers Comput. Neurosci. 18 (2024) - [j8]Kai Arulkumaran, Marina Di Vincenzo, Rousslan Fernand Julien Dossa, Shogo Akiyama, Dan Ogawa Lillrank, Motoshige Sato, Kenichi Tomeoka, Shuntaro Sasai:
A comparison of visual and auditory EEG interfaces for robot multi-stage task control. Frontiers Robotics AI 11 (2024) - [j7]Roberto Gallotta
, Kai Arulkumaran, Lisa B. Soros:
Preference-Learning Emitters for Mixed-Initiative Quality-Diversity Algorithms. IEEE Trans. Games 16(2): 303-316 (2024) - 2022
- [j6]Tianhong Dai, Kai Arulkumaran, Tamara Gerbert, Samyakh Tukra, Feryal M. P. Behbahani, Anil Anthony Bharath:
Analysing deep reinforcement learning agents trained with domain randomisation. Neurocomputing 493: 143-165 (2022) - [j5]Arthur Juliani, Kai Arulkumaran, Shuntaro Sasai, Ryota Kanai:
On the link between conscious function and general intelligence in humans and machines. Trans. Mach. Learn. Res. 2022 (2022) - 2021
- [j4]Jess Whittlestone, Kai Arulkumaran, Matthew Crosby:
The Societal Implications of Deep Reinforcement Learning. J. Artif. Intell. Res. 70: 1003-1030 (2021) - 2018
- [j3]Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sengupta, Anil A. Bharath:
Generative Adversarial Networks: An Overview. IEEE Signal Process. Mag. 35(1): 53-65 (2018) - 2017
- [j2]Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath:
Deep Reinforcement Learning: A Brief Survey. IEEE Signal Process. Mag. 34(6): 26-38 (2017) - 2016
- [j1]Jose Rivera-Rubio, Kai Arulkumaran, Hemang Rishi, Ioannis Alexiou, Anil A. Bharath:
An assistive haptic interface for appearance-based indoor navigation. Comput. Vis. Image Underst. 149: 126-145 (2016)
Conference and Workshop Papers
- 2023
- [c12]Kai Arulkumaran, Dan Ogawa Lillrank:
A Pragmatic Look at Deep Imitation Learning. ACML 2023: 58-73 - 2022
- [c11]Roberto Gallotta, Kai Arulkumaran, Lisa B. Soros:
Surrogate Infeasible Fitness Acquirement FI-2Pop for Procedural Content Generation. CoG 2022: 500-503 - [c10]Kai Arulkumaran, Thu Nguyen-Phuoc:
Minimal criterion artist collective. GECCO Companion 2022: 687-690 - [c9]Roberto Gallotta, Kai Arulkumaran, Lisa B. Soros:
Evolving spaceships with a hybrid L-system constrained optimisation evolutionary algorithm. GECCO Companion 2022: 711-714 - 2021
- [c8]Tianhong Dai, Hengyan Liu, Kai Arulkumaran, Guangyu Ren, Anil Anthony Bharath:
Diversity-Based Trajectory and Goal Selection with Hindsight Experience Replay. PRICAI (3) 2021: 32-45 - 2020
- [c7]Manon Flageat, Kai Arulkumaran, Anil A. Bharath:
Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. ESANN 2020: 229-234 - [c6]Kevin Pan, Guillem Hurault, Kai Arulkumaran, Hywel C. Williams, Reiko J. Tanaka:
EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis. MLMI@MICCAI 2020: 220-230 - 2019
- [c5]Kai Arulkumaran, Antoine Cully, Julian Togelius:
AlphaStar: an evolutionary computation perspective. GECCO (Companion) 2019: 314-315 - [c4]Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori:
Adaptive Neural Trees. ICML 2019: 6166-6175 - [c3]Shafa Balaram, Kai Arulkumaran, Tianhong Dai, Anil Anthony Bharath:
A Maximum Entropy Deep Reinforcement Learning Neural Tracker. MLMI@MICCAI 2019: 400-408 - [c2]Cher Bass, Tianhong Dai, Benjamin Billot, Kai Arulkumaran, Antonia Creswell, Claudia Clopath, Vincenzo De Paola, Anil Anthony Bharath:
Image Synthesis with a Convolutional Capsule Generative Adversarial Network. MIDL 2019: 39-62 - [c1]Tianhong Dai, Magda Dubois, Kai Arulkumaran, Jonathan Campbell, Cher Bass, Benjamin Billot, Fatmatülzehra Uslu, Vincenzo De Paola, Claudia Clopath, Anil Anthony Bharath:
Deep Reinforcement Learning for Subpixel Neural Tracking. MIDL 2019: 130-150
Informal and Other Publications
- 2024
- [i22]Motoshige Sato, Kenichi Tomeoka, Ilya Horiguchi, Kai Arulkumaran, Ryota Kanai, Shuntaro Sasai:
Scaling Law in Neural Data: Non-Invasive Speech Decoding with 175 Hours of EEG Data. CoRR abs/2407.07595 (2024) - 2022
- [i21]Kai Arulkumaran, Dylan R. Ashley, Jürgen Schmidhuber, Rupesh Kumar Srivastava:
All You Need Is Supervised Learning: From Imitation Learning to Meta-RL With Upside Down RL. CoRR abs/2202.11960 (2022) - [i20]Dylan R. Ashley, Kai Arulkumaran, Jürgen Schmidhuber, Rupesh Kumar Srivastava:
Learning Relative Return Policies With Upside-Down Reinforcement Learning. CoRR abs/2202.12742 (2022) - [i19]Arthur Juliani, Kai Arulkumaran, Shuntaro Sasai, Ryota Kanai:
On the link between conscious function and general intelligence in humans and machines. CoRR abs/2204.05133 (2022) - [i18]Roberto Gallotta, Kai Arulkumaran, Lisa B. Soros:
Surrogate Infeasible Fitness Acquirement FI-2Pop for Procedural Content Generation. CoRR abs/2205.05834 (2022) - [i17]Roberto Gallotta, Kai Arulkumaran, Lisa B. Soros:
Preference-Learning Emitters for Mixed-Initiative Quality-Diversity Algorithms. CoRR abs/2210.13839 (2022) - 2021
- [i16]Kai Arulkumaran, Dan Ogawa Lillrank:
A Pragmatic Look at Deep Imitation Learning. CoRR abs/2108.01867 (2021) - [i15]Tianhong Dai, Hengyan Liu, Kai Arulkumaran, Guangyu Ren, Anil Anthony Bharath:
Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay. CoRR abs/2108.07887 (2021) - 2020
- [i14]Pierre-Alexandre Kamienny, Kai Arulkumaran, Feryal M. P. Behbahani, Wendelin Boehmer, Shimon Whiteson:
Privileged Information Dropout in Reinforcement Learning. CoRR abs/2005.09220 (2020) - 2019
- [i13]Kai Arulkumaran, Antoine Cully, Julian Togelius:
AlphaStar: An Evolutionary Computation Perspective. CoRR abs/1902.01724 (2019) - [i12]Andrea Agostinelli, Kai Arulkumaran, Marta Sarrico, Pierre Richemond, Anil Anthony Bharath:
Memory-Efficient Episodic Control Reinforcement Learning with Dynamic Online k-means. CoRR abs/1911.09560 (2019) - [i11]Marta Sarrico, Kai Arulkumaran, Andrea Agostinelli, Pierre Richemond, Anil Anthony Bharath:
Sample-Efficient Reinforcement Learning with Maximum Entropy Mellowmax Episodic Control. CoRR abs/1911.09615 (2019) - [i10]Tianhong Dai, Kai Arulkumaran, Samyakh Tukra, Feryal M. P. Behbahani, Anil Anthony Bharath:
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation. CoRR abs/1912.08324 (2019) - 2018
- [i9]Sebastian Tschiatschek, Kai Arulkumaran, Jan Stühmer, Katja Hofmann:
Variational Inference for Data-Efficient Model Learning in POMDPs. CoRR abs/1805.09281 (2018) - [i8]Ryutaro Tanno, Kai Arulkumaran, Daniel C. Alexander, Antonio Criminisi, Aditya V. Nori:
Adaptive Neural Trees. CoRR abs/1807.06699 (2018) - 2017
- [i7]Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, Anil Anthony Bharath:
A Brief Survey of Deep Reinforcement Learning. CoRR abs/1708.05866 (2017) - [i6]Antonia Creswell, Kai Arulkumaran, Anil A. Bharath:
On denoising autoencoders trained to minimise binary cross-entropy. CoRR abs/1708.08487 (2017) - [i5]Antonia Creswell, Tom White, Vincent Dumoulin, Kai Arulkumaran, Biswa Sengupta, Anil A. Bharath:
Generative Adversarial Networks: An Overview. CoRR abs/1710.07035 (2017) - 2016
- [i4]Kai Arulkumaran, Nat Dilokthanakul, Murray Shanahan, Anil Anthony Bharath:
Classifying Options for Deep Reinforcement Learning. CoRR abs/1604.08153 (2016) - [i3]Marta Garnelo, Kai Arulkumaran, Murray Shanahan:
Towards Deep Symbolic Reinforcement Learning. CoRR abs/1609.05518 (2016) - [i2]Kai Arulkumaran, Antonia Creswell, Anil Anthony Bharath:
Improving Sampling from Generative Autoencoders with Markov Chains. CoRR abs/1610.09296 (2016) - [i1]Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew C. H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan:
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders. CoRR abs/1611.02648 (2016)
Coauthor Index
aka: Anil Anthony Bharath
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-13 00:43 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
