Talks

Implicit Representations Seminar
University of Oxford, OATML seminar - June 2022
Interventions Where and How? Causal Experimental Design at Scale
Wellcome Centre of Human Neuroimaging, UCL - April 2022
Active Inference Seminar
University of Oxford, OATML seminar - Feb 2021
Robust Autonomous Driving
Google-Oxford workshop, November 2020
Qualcomm, Research talk, November 2020
Artificial Intelligence in Art & Design
Bartlett School of Architecture, UCL, London - Feb 2019
Department of Fine Art, U. of Ioannina, Greece - Nov 2019

Publications / Technical Reports

2024
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
Amir Mohammad Karimi Mamaghan, Panagiotis Tigas, Karl Henrik Johansson, Yarin Gal, Yashas Annadani, Stefan Bauer
ICML 2024
PDF bibtex
Amortized Active Causal Induction with Deep Reinforcement Learning
Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster
PDF bibtex
2023
Differentiable multi-target causal bayesian experimental design
Differentiable multi-target causal bayesian experimental design
Panagiotis Tigas*, Yashas Annadani*, Desi R Ivanova, Andrew Jesson, Yarin Gal, Adam Foster, Stefan Bauer
ICML 2023
PDF bibtex
2022
Global geomagnetic perturbation forecasting using Deep Learning
Global geomagnetic perturbation forecasting using Deep Learning
Vishal Upendran, Panagiotis Tigas, Banafsheh Ferdousi, Teo Bloch, Mark CM Cheung, Siddha Ganju, Asti Bhatt, Ryan M McGranaghan, Yarin Gal
Space Weather
PDF bibtex
Interventions, Where and How? Experimental Design for Causal Models at Scale
Interventions, Where and How? Experimental Design for Causal Models at Scale
Panagiotis Tigas*, Yashas Annadani*, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer
NeurIPS 2022
PDF bibtex
2021
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
Andrew Jesson*, Panagiotis Tigas*, Joost van Amersfoort, Andreas Kirsch, Uri Shalit, Yarin Gal
NeurIPS 2021
PDF bibtex
Exploration and preference satisfaction trade-off in reward-free learning
Exploration and preference satisfaction trade-off in reward-free learning
Noor Sajid, Panagiotis Tigas Alexey Zakharov, Zafeirios Fountas, Karl Friston
ICML 2021 Workshop on Unsupervised Reinforcement Learning
PDF bibtex
Latent Mappings: Generating open-ended expressive mappings using Variational Autoencoders
Latent Mappings: Generating open-ended expressive mappings using Variational Autoencoders
Tim Murray-Browne, Panagiotis Tigas
2021 New Interfaces for Musical Expression (NIME)
PDF
2020
Global Earth Magnetic Field Modeling andForecasting with Spherical Harmonics Decomposition
Global Earth Magnetic Field Modeling andForecasting with Spherical Harmonics Decomposition
Panagiotis Tigas*, Téo Bloch*, Vishal Upendran*, Banafsheh Ferdoushi*, Mark C. M. Cheung, Siddha Ganju, Ryan M. McGranaghan, Yarin Gal, Asti Bhatt
Machine Learning and the Physical Sciences Workshop - 34th NeurIPS 2020
PDF
Real2sim: Automatic Generation of Open Street Map Towns For Autonomous Driving Benchmarks
Real2sim: Automatic Generation of Open Street Map Towns For Autonomous Driving Benchmarks
Avishek Mandal, Panagiotis Tigas, Yarin Gal
Machine Learning for Autonomous Driving Workshop at the 34rd Conference on Neural Information Processing Systems (NeurIPS 2020)
PDF
Spatial Assembly:Generative Architecture With Reinforcement Learning, Self Play and Tree Search
Spatial Assembly:Generative Architecture With Reinforcement Learning, Self Play and Tree Search
Panagiotis Tigas, Tyson Hosmer
Workshop on Machine Learning for Creativity and Design at the 34rd Conference on Neural Information Processing Systems (NeurIPS 2020)
PDF
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Angelos Filos*, Panagiotis Tigas*, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal
37th International Conference on Machine Learning (ICML 2020)
PDF bibtex
Percival: Making In-browser Perceptual Ad Blocking Practical with Deep Learning
Percival: Making In-browser Perceptual Ad Blocking Practical with Deep Learning
Zain ul Abi Din, Panagiotis Tigas, Samuel T. King, Benjamin Livshits
USENIX ATC, 2020 (Acceptance rate 18.6%)
PDF bibtex
2019
Robust Imitative Planning: Planning from Demonstrations Under Uncertainty
Robust Imitative Planning: Planning from Demonstrations Under Uncertainty
Panagiotis Tigas*, Angelos Filos*, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal
Machine Learning for Autonomous Driving Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada.
PDF bibtex
Towards an Autonomous Architecture
Towards an Autonomous Architecture
Tyson Hosmer, Panagiotis Tigas
Association for Computer Aided Design In Architecture (ACADIA), 2019 (acceptance rate ~25%) - Emerging Research Award
PDF bibtex
2014
The Cave Of Sounds: An Interactive Installation Exploring How We Create Music Together
The Cave Of Sounds: An Interactive Installation Exploring How We Create Music Together
Tim Murray-Browne, Dom Aversano, Susanna Garcia, Wallace Hobbes, Daniel Lopez, Tadeo Sendon, Panagiotis Tigas, Kacper Ziemianin, Duncan Chapman
International Conference on New Interfaces for Musical Expression (NIME), 2014
PDF bibtex
2012
Markovjam: Real-time jam-session support system
Markovjam: Real-time jam-session support system
Panagiotis Tigas
MSc Thesis (2012)
PDF bibtex