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02/21/2023
Differentiable Multi-Target Causal Bayesian Experimental Design
We introduce a gradient-based approach for the problem of Bayesian optim...
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07/25/2022
Modelling non-reinforced preferences using selective attention
How can artificial agents learn non-reinforced preferences to continuous...
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03/03/2022
Interventions, Where and How? Experimental Design for Causal Models at Scale
Causal discovery from observational and interventional data is challengi...
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11/03/2021
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
Estimating personalized treatment effects from high-dimensional observat...
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06/16/2021
Latent Mappings: Generating Open-Ended Expressive Mappings Using Variational Autoencoders
In many contexts, creating mappings for gestural interactions can form p...
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06/08/2021
Exploration and preference satisfaction trade-off in reward-free learning
Biological agents have meaningful interactions with their environment de...
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02/02/2021
Global Earth Magnetic Field Modeling and Forecasting with Spherical Harmonics Decomposition
Modeling and forecasting the solar wind-driven global magnetic field per...
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01/19/2021
Spatial Assembly: Generative Architecture With Reinforcement Learning, Self Play and Tree Search
With this work, we investigate the use of Reinforcement Learning (RL) fo...
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06/26/2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?
Out-of-training-distribution (OOD) scenarios are a common challenge of l...
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05/17/2019
