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Panagiotis Tigas
Panagiotis Tigas
Isomoprhic Labs, Oxford University
Bestätigte E-Mail-Adresse bei robots.ox.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
A Filos, P Tigas, R McAllister, N Rhinehart, S Levine, Y Gal
ICML 2020, 2020
2392020
Shifts: A dataset of real distributional shift across multiple large-scale tasks
A Malinin, N Band, G Chesnokov, Y Gal, MJF Gales, A Noskov, ...
arXiv preprint arXiv:2107.07455, 2021
1552021
Interventions, Where and How? Experimental Design for Causal Models at Scale
P Tigas, Y Annadani, A Jesson, B Schölkopf, Y Gal, S Bauer
Neural Information Processing Systems 35 (1), 2022
472022
PERCIVAL: Making In-Browser Perceptual Ad Blocking Practical with Deep Learning
Z Abi Din, P Tigas, ST King, B Livshits
2020 USENIX Annual Technical Conference (USENIX ATC 20), 387-400, 2020
39*2020
Causal-bald: Deep bayesian active learning of outcomes to infer treatment-effects from observational data
A Jesson, P Tigas, J van Amersfoort, A Kirsch, U Shalit, Y Gal
Advances in Neural Information Processing Systems 34, 30465-30478, 2021
352021
Exploration and preference satisfaction trade-off in reward-free learning
N Sajid, P Tigas, A Zakharov, Z Fountas, K Friston
arXiv preprint arXiv:2106.04316, 2021
272021
Differentiable multi-target causal bayesian experimental design
P Tigas, Y Annadani, DR Ivanova, A Jesson, Y Gal, A Foster, S Bauer
International Conference on Machine Learning, 34263-34279, 2023
17*2023
Deep Reinforcement Learning for Autonomous Robotic Tensegrity (ART)
T Hosmer, P Tigas
39th Annual Conference of the Association for Computer Aided Design in …, 2019
142019
Global geomagnetic perturbation forecasting using Deep Learning
V Upendran, P Tigas, B Ferdousi, T Bloch, MCM Cheung, S Ganju, ...
Space Weather, e2022SW003045, 2022
12*2022
Spatial Assembly: Generative Architecture With Reinforcement Learning, Self Play and Tree Search
P Tigas, T Hosmer
Workshop on Machine Learning for Creativity and Design at the 34rd …, 2020
12*2020
Active inference, preference learning and adaptive behaviour
N Sajid, P Tigas, K Friston
IOP Conference Series: Materials Science and Engineering 1261 (1), 012020, 2022
92022
The Cave Of Sounds: An Interactive Installation Exploring How We Create Music Together
T Murray-Browne, D Aversano, S Garcia, W Hobbes, D Lopez, T Sendon, ...
NIME, 2014
92014
Emergent interfaces: Vague, complex, bespoke and embodied interaction between humans and computers
T Murray-Browne, P Tigas
Applied Sciences 11 (18), 8531, 2021
82021
Challenges and considerations in the evaluation of bayesian causal discovery
AM Karimi Mamaghan, P Tigas, KH Johansson, Y Gal, Y Annadani, ...
arXiv e-prints, arXiv: 2406.03209, 2024
6*2024
Real2sim: Automatic Generation of Open Street Map Towns For Autonomous Driving Benchmarks
A Mondal, P Tigas, Y Gal
62020
Deep bayesian active learning for preference modeling in large language models
L Carvalho Melo, P Tigas, A Abate, Y Gal
Advances in Neural Information Processing Systems 37, 118052-118085, 2024
42024
Amortized active causal induction with deep reinforcement learning
Y Annadani, P Tigas, S Bauer, A Foster
Advances in Neural Information Processing Systems 37, 44216-44239, 2024
22024
A Multilevel Low-Rank Newton Method with Super-linear Convergence Rate and its Application to Non-convex Problems
N Tsipinakis, P Tigkas, P Parpas
arXiv preprint arXiv:2305.08742, 2023
22023
Modelling non-reinforced preferences using selective attention
N Sajid, P Tigas, Z Fountas, Q Guo, A Zakharov, L Da Costa
arXiv preprint arXiv:2207.13699, 2022
12022
Unravelling A Regulation Machine: Fake News, Toxic Comments And'Illegitimate'Culture
D Mylonaki, P Tigas
A Peer-Reviewed Journal About 7 (1), 86-98, 2018
12018
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