Tigas, Panagiotis

10 publications

NeurIPS 2024 Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster

ICMLW 2024 Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani, Panagiotis Tigas, Stefan Bauer, Adam Foster

ICML 2024 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

NeurIPS 2024 Deep Bayesian Active Learning for Preference Modeling in Large Language Models Luckeciano C. Melo, Panagiotis Tigas, Alessandro Abate, Yarin Gal

NeurIPSW 2024 Efficient Experimentation for Estimation of Continuous and Discrete Conditional Treatment Effects Muhammed Razzak, Panagiotis Tigas, Andrew Jesson, Yarin Gal, Uri Shalit

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

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

NeurIPS 2022 Interventions, Where and How? Experimental Design for Causal Models at Scale Panagiotis Tigas, Yashas Annadani, Andrew Jesson, Bernhard Schölkopf, Yarin Gal, Stefan Bauer

NeurIPS 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, Uri Shalit, Yarin Gal

ICMLW 2021 Exploration and Preference Satisfaction Trade-Off in Reward-Free Learning Noor Sajid, Panagiotis Tigas, Alexey Zakharov, Zafeirios Fountas, Karl Friston