Hi there 👋 My name is Adrián, and I am a PhD student at the Probabilistic Machine Learning group under the supervision of Isabel Valera at Saarland University. I am also an alumnus of the Empirical Inference department at the Max Planck Institute for Intelligent Systems. Before pursuing my PhD, I completed a Master in Computer Science and a double Bachelor Degree in Computer Science Engineering and Mathematics at the University of Murcia.
I am mostly interested in principled research that aims to improve machine learning methods, making them easier to use and more robust. Specifically, my current research focuses on improving models that optimize different tasks simultaneously. This includes apparently unrelated areas such as multitask learning (MTL) and deep probabilistic generative models (e.g. VAEs) under heterogeneous environments.
However, I am a curiosity-driven, and I am always happy to discuss interesting ideas even if they lie outside my comfort zone. Feel free to reach me out via Twitter or email.
Causal normalizing flows: from theory to practice Journal Article
In: CoRR, vol. abs/2306.05415, 2023.
Learnable Graph Convolutional Attention Networks Proceedings Article
In: The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, OpenReview.net, 2023.
In: CoRR, vol. abs/2206.04496, 2022.
RotoGrad: Gradient Homogenization in Multitask Learning Proceedings Article
In: The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, OpenReview.net, 2022.
Lipschitz standardization for robust multivariate learning Journal Article
In: CoRR, vol. abs/2002.11369, 2020.
In: CoRR, vol. abs/2006.15090, 2020.
In: CoRR, vol. abs/1903.02642, 2019.