Helena Andres Terre
Helena Andres Terre

PhD Artificial Intelligence and Machine Learning. Complex systems researcher. Physicist. (she/her/hers)

  • Home
  • About me
  • Research
  • Experience
  • Publications
  • Outside the lab

    Recent publications

    Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches

    Dmitry Kazhdan, Botty Dimanov, Helena Andres Terre, Mateja Jamnik, Pietro Lio, Adrian Weller
    RAI ICLR
    2021

    REM: An Integrative Rule Extraction Methodology for Explainable Data Analysis in Healthcare

    Zohreh Shams, Botty Dimanov, Sumaiyah Kola, Nikola Simidjievski, Helena Andres Terre, Paul Scherer, Urska Matjasec, Jean Abraham, Pietro Liò, Mateja Jamnik
    medRxiv, preprint doi: 2021.01.25.21250459 (under revision)
    2021

    Adversarial generation of gene expression data

    Ramon Viñas, Helena Andres-Terre, Pietro Lio, and Kevin Bryson
    Bioinformatics
    2021

    Using ontology embeddings for structural inductive bias in gene expression data analysis

    Maja Trębacz, Zohreh Shams, Mateja Jamnik, Paul Scherer, Nikola Simidjievski, Helena Andres Terre, Pietro Lio
    MLCB
    2020

    Incorporating network based protein complex discovery into automated model construction

    Paul Scherer, Maja Trȩbacz, Nikola Simidjievski, Zohreh Shams, Helena Andres Terre, Pietro Lio, Mateja Jamnik
    MLCB
    2020

    CellVGAE: An unsupervised scRNA-seq analysis workflow with graph attention networks

    David Buterez, Ioana Bica, Ifrah Tariq, Helena Andres-Terre, Pietro Lio
    bioRxiv doi: 12.20.423645
    2020

    Unsupervised generative and graph representation learning for modelling cell differentiation.

    Bica *, I. , Andres-Terre *, H. , Cvejic, A., Lio, P.
    Scientic Reports
    2019

    Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice.

    Simifjievski, N. , Bodnar, C. , Tariq, I. , Scherer, P. , Andres-Terre, H., Shams, Z., Jamnik, M. , Lio, P.
    Frontiers in Genetics.
    2019

    Decoupling feature propagation from the design of graph auto-encoders

    Scherer, P., Andres-Terre, H., Lio, P., Jamnik, M.
    arXiv:1910.08589
    2019

    Adversarial generation of gene expression data

    Viñas, R., Andrés-Terré, H., Liò, P., Bryson, K.
    bioRxiv, 836254.
    2019

    Factorised Neural Relational Inference for Multi-Interaction Systems.

    Webb, E., Day, B., Andres-Terre, H., Li, P.
    ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Representations.
    arXiv, preprint arXiv:1905.08721.
    2019

    Single-cell RNA-sequencing uncovers transcriptional states and fate decisions in haematopoiesis.

    Athanasiadis, E. I., Botthof, J. G., Andres, H., Ferreira, L., Lio, P., Cvejic, A.
    Nature communications, 8(1), 2045.
    2017

    Perturbation theory approach to study the latent space degeneracy of Variational Autoencoders.

    Andres-Terre, H. Lio, P.
    arXiv, preprint arXiv:1907.05267
    2019

    GEESE: Metabolically driven latent space learning for gene expression data.

    Barsacchi, M., Andres-Terre, H., Li, P.
    bioRxiv, 365643.
    2018

    Talks & Conferences

    Cloud Computing and DataBases

    2 day course @Cambridge Spark
    April 2020

    Introduction to Variational Autoencoders

    talk @Cambridge Spark
    March 2020

    AI for Medical Data

    1 day course @CamBioScience
    March 2020

    Multi-modal cancer data integration

    talk @the Mark Foundation
    January 2020

    AI for cancer Data Integration

    talk @the Mark Foundation
    September 2019

    AI and Deep Learning, the basics

    talk @Newnham College
    March 2019

    Variational Autoencoders to decipher Stem Cell differentiation

    poster @NIPS2018 - Workshop for Women in Machine Learning.
    December 2018

    Single Cell RNA-Seq analysis through VAEs

    talk @Big Data Symposium, Cambridge Data Science
    November 2018

    Unsupervised learning and cell differentiation

    talk @BenevolentAI
    September 2018

    Decoding biology through variational autoencoders

    talk @International Conference on Complex Systems 2018
    July 2018

    Unsupervised learning and Stem Cell Differentiation; Autoencoders and Single Cell data

    talk @Oxbridge Women in CS Conference
    March 2018

    gRE:MLIN, multilayer extension of the Reasoning Engine for Interaction Networks

    talk @Microsoft Research
    September 2016

    Explosive Synchronisation within the Kuramoto model

    talk @Mediterranean School of Complex Networks
    June 2014

    The Electrophysiology of Stem Cells Using Conductive Atomic Force Microscopy

    poster @Rensselaer Polytechnic Institute Research Forum
    June 2013