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Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

A. Filos, P. Tigas, R. McAllister, N. Rhinehart, S. Levine, and Y. Gal. ICML, volume 119 of Proceedings of Machine Learning Research, page 3145-3153. PMLR, (2020)

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Panagiotis Theodorou

Panagiotis Mitsakis

Panagiotis Zacharopoulos

Panagiotis Aslanidis

Panagiotis Pashalidis

Other publications of authors with the same name

Interventions, Where and How? Experimental Design for Causal Models at Scale.P. Tigas, Y. Annadani, A. Jesson, B. Schölkopf, Y. Gal, and S. Bauer. NeurIPS, (2022)Latent Mappings: Generating Open-Ended Expressive Mappings Using Variational Autoencoders.T. Browne, and P. Tigas. NIME, nime.org, (2021)Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks.A. Malinin, N. Band, Y. Gal, M. Gales, A. Ganshin, G. Chesnokov, A. Noskov, A. Ploskonosov, L. Prokhorenkova, I. Provilkov and 6 other author(s). NeurIPS Datasets and Benchmarks, (2021)Amortized Active Causal Induction with Deep Reinforcement Learning.Y. Annadani, P. Tigas, S. Bauer, and A. Foster. CoRR, (2024)Exploration and preference satisfaction trade-off in reward-free learning.N. Sajid, P. Tigas, A. Zakharov, Z. Fountas, and K. Friston. CoRR, (2021)Percival: Making In-Browser Perceptual Ad Blocking Practical With Deep Learning.Z. ul Abi Din, P. Tigas, S. King, and B. Livshits. CoRR, (2019)Deep Bayesian Active Learning for Preference Modeling in Large Language Models.L. Melo, P. Tigas, A. Abate, and Y. Gal. CoRR, (2024)The Cave of Sounds: An Interactive Installation Exploring How We Create Music Together.T. Browne, D. Aversano, S. Garcia, W. Hobbes, D. Lopez, T. Sendon, P. Tigas, K. Ziemianin, and D. Chapman. NIME, page 307-310. nime.org, (2014)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, and Y. Gal. NeurIPS, page 30465-30478. (2021)Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?A. Filos, P. Tigas, R. McAllister, N. Rhinehart, S. Levine, and Y. Gal. ICML, volume 119 of Proceedings of Machine Learning Research, page 3145-3153. PMLR, (2020)

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Disambiguation of "Tigas, Panagiotis"

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Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

Please choose a person to relate this publication to

Panagiotis Theodorou

Panagiotis Mitsakis

Panagiotis Zacharopoulos

Panagiotis Aslanidis

Panagiotis Pashalidis

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Tigas, Panagiotis"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

Please choose a person to relate this publication to

Panagiotis Theodorou

Panagiotis Mitsakis

Panagiotis Zacharopoulos

Panagiotis Aslanidis

Panagiotis Pashalidis

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?