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 (NIME, 2014)

Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? - Angelos Filos; Panagiotis Tigas; Rowan McAllister; Nicholas Rhinehart; Sergey Levine; Yarin Gal (ICML, 2020)

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)

Latent Mappings: Generating Open-Ended Expressive Mappings Using Variational Autoencoders. - Tim Murray Browne; Panagiotis Tigas (NIME, 2021)

Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data. - Andrew Jesson; Panagiotis Tigas; Joost van Amersfoort; Andreas Kirsch 002; Uri Shalit; Yarin Gal (NeurIPS, 2021)

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks. - Andrey Malinin; Neil Band; Yarin Gal; Mark J. F. Gales; Alexander Ganshin; German Chesnokov; Alexey Noskov; Andrey Ploskonosov; Liudmila Prokhorenkova; Ivan Provilkov; Vatsal Raina; Vyas Raina; et al. (NeurIPS Datasets and Benchmarks, 2021)

Spatial Assembly: Generative Architecture With Reinforcement Learning, Self Play and Tree Search. - Panagiotis Tigas; Tyson Hosmer (CoRR, 2021)

Global Earth Magnetic Field Modeling and Forecasting 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 (CoRR, 2021)

Exploration and preference satisfaction trade-off in reward-free learning. - Noor Sajid; Panagiotis Tigas; Alexey Zakharov; Zafeirios Fountas; Karl J. Friston (CoRR, 2021)

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)

Global geomagnetic perturbation forecasting using Deep Learning. - Vishal Upendran; Panagiotis Tigas; Banafsheh Ferdousi; Téo Bloch; Mark C. M. Cheung; Siddha Ganju; Asti Bhatt; Ryan M. McGranaghan; Yarin Gal (CoRR, 2022)

Modelling non-reinforced preferences using selective attention. - Noor Sajid; Panagiotis Tigas; Zafeirios Fountas; Qinghai Guo; Alexey Zakharov; Lancelot Da Costa (CoRR, 2022)

Differentiable Multi-Target Causal Bayesian Experimental Design. - Panagiotis Tigas; Yashas Annadani; Desi R. Ivanova; Andrew Jesson; Yarin Gal; Adam Foster 001; Stefan Bauer (ICML, 2023)

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)

Amortized Active Causal Induction with Deep Reinforcement Learning. - Yashas Annadani; Panagiotis Tigas; Stefan Bauer; Adam Foster 001 (NeurIPS, 2024)

Deep Bayesian Active Learning for Preference Modeling in Large Language Models. - Luckeciano Carvalho Melo; Panagiotis Tigas; Alessandro Abate; Yarin Gal (NeurIPS, 2024)