Anssi Kanervisto
Anssi Kanervisto
Researcher, Microsoft Research
Verified email at - Homepage
Cited by
Cited by
Stable baselines
A Hill, A Raffin, M Ernestus, A Gleave, A Kanervisto, R Traore, P Dhariwal, ...
Stable-baselines3: Reliable reinforcement learning implementations
A Raffin, A Hill, A Gleave, A Kanervisto, M Ernestus, N Dormann
The Journal of Machine Learning Research 22 (1), 12348-12355, 2021
Stable baselines3
A Raffin, A Hill, M Ernestus, A Gleave, A Kanervisto, N Dormann
Image-to-markup generation with coarse-to-fine attention
Y Deng, A Kanervisto, J Ling, AM Rush
ICML 2017, 2017
Action Space Shaping in Deep Reinforcement Learning
A Kanervisto, C Scheller, V Hautamäki
IEEE Conference on Games 2020, 2020
Multi-task Learning with Attention for End-to-end Autonomous Driving
K Ishihara, A Kanervisto, J Miura, V Hautamäki
CVPR 2021 Workshop on Autonomous Driving, 2021
The I4U mega fusion and collaboration for NIST speaker recognition evaluation 2016
KA Lee, V Hautamaki, A Larcher, C Zhang, A Nautsch, T Stafylakis, G Liu, ...
Interspeech 2017, 2017
The 37 implementation details of proximal policy optimization
S Huang, RFJ Dossa, A Raffin, A Kanervisto, W Wang
The ICLR Blog Track 2023, 2022
The MineRL BASALT competition on learning from human feedback
R Shah, C Wild, SH Wang, N Alex, B Houghton, W Guss, S Mohanty, ...
arXiv preprint arXiv:2107.01969, 2021
Stable baselines3 (2019)
A Raffin, A Hill, M Ernestus, A Gleave, A Kanervisto, N Dormann
URL https://github. com/DLR-RM/stable-baselines3, 0
Effects of gender information in text-independent and text-dependent speaker verification
A Kanervisto, V Vestman, M Sahidullah, V Hautamäki, T Kinnunen
ICASSP 2017, 2017
Benchmarking End-to-End Behavioural Cloning on Video Games
A Kanervisto, J Pussinen, V Hautamäki
IEEE Conference on Games 2020, 2020
Optimizing tandem speaker verification and anti-spoofing systems
A Kanervisto, V Hautamäki, T Kinnunen, J Yamagishi
IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 477-488, 2021
Imitating human behaviour with diffusion models
T Pearce, T Rashid, A Kanervisto, D Bignell, M Sun, R Georgescu, ...
arXiv preprint arXiv:2301.10677, 2023
Minerl diamond 2021 competition: Overview, results, and lessons learned
A Kanervisto, S Milani, K Ramanauskas, N Topin, Z Lin, J Li, J Shi, D Ye, ...
NeurIPS 2021 Competitions and Demonstrations Track, 13-28, 2022
Playing Minecraft with Behavioural Cloning
A Kanervisto, J Karttunen, V Hautamäki
NeurIPS 2019 Post Proceedings of the Competitions & Demonstrations Track, 2020
From Video Game to Real Robot: The Transfer between Action Spaces
J Karttunen, A Kanervisto, V Hautamäki, V Kyrki
ICASSP 2020, 2019
Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020
WH Guss, S Milani, N Topin, B Houghton, S Mohanty, A Melnik, A Harter, ...
NeurIPS 2020 Competition and Demonstration Track, 233-252, 2021
Do autonomous agents benefit from hearing?
A Woubie, A Kanervisto, J Karttunen, V Hautamaki
arXiv preprint arXiv:1905.04192, 2019
Who Do I Sound Like? Showcasing Speaker Recognition Technology by YouTube Voice Search
V Vestman, B Soomro, A Kanervisto, V Hautamäki, T Kinnunen
ICASSP 2019, 2018
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