Ignacio Peis

Postdoctoral Researcher

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Contact:

Building 321, Office 220

Richard Petersens Plads

2800 Kgs Lyngby, Denmark 🇩🇰

ipeaz@dtu.dk




Section for Cognitive Systems
Department of Applied Mathematics and Computer Science
Technical University of Denmark (DTU)

Pioneer Centre for Artificial Intelligence

About   I am a postdoctoral researcher at the Section for Cognitive Systems, in Technical University of Denmark (DTU). I work within Jes Frellsen’s group, where we embark on a range of fascinating projects.

Research   I am interested in the connection between Deep Learning and Probabilistic Modelling. My current research lies in creating more expressive generative models, increasing their robustness and developing better inference methods. My work has been applied to several fields, like Neuroscience, Physics or Psychiatry.

Short Bio   I completed my PhD in Probabilistic Machine Learning at UC3M, where I was supervised by Prof. Antonio Artés-Rodríguez and Dr. Pablo M. Olmos from the Signal Processing Group. Previously, I was a research intern at the Machine Learning Group in the Department of the Engineering, University of Cambridge where I worked with Prof. José Miguel Hernández-Lobato. I obtained two MSc degrees in Telecommunications Engineering and Signal Processing from UC3M, and a BSc degree in Telecommunications Engineering from UGR.

news

Apr 24, 2025 New preprint available! “Hyper-Transforming Latent Diffusion Models”
[prepint]
Apr 24, 2025 I gave a talk about my latest research at CITIC, Universidad de Granada. Find here a link to the slides.
Apr 22, 2025 [AISTATS25] I have received the Best Reviewer Award at AISTATS 2025!
Nov 01, 2024 [NeurIPS24] I have been selected as Top Reviewer at NeurIPS 2024!
May 07, 2024 New preprint available! “Scalable physical source-to-field inference with hypernetworks”
[prepint]

selected publications

  1. Variational Mixture of HyperGenerators for Learning Distributions Over Functions
    In Proceedings of the 40th International Conference on Machine Learning, 2023
  2. Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte Carlo
    Ignacio Peis, Chao Ma, and José Miguel Hernández-Lobato
    In Advances in Neural Information Processing Systems 35, 2022
  3. PR
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    Unsupervised learning of global factors in deep generative models
    Ignacio Peis, Pablo M. Olmos, and Antonio Artés-Rodríguez
    Pattern Recognition, 2022