Mateo Rojas-Carulla
Building the safety layer for AI at Lakera. Ex-Google, PhD @ Cambridge/MPI.
Building the safety layer for AI at Lakera. Ex-Google, PhD @ Cambridge/MPI.
Homeyer et. al. Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology. Modern Pathology 2022.
A. Hawkins, G. Visona, T. Narendra, MRC, B. Schölkopf, G. Schweikert. Getting Personal with Epigenetics: Towards Machine-Learning Assisted Precision Epigenomics.
O. Mineeva*, MRC*, R. Ley, B. Schölkopf, N. Youngblut. DeepMAsED: Evaluating the Quality of Metagenomic Assemblies. Bioinformatics 2020. Code.
MRC. Learning Transferable Representations. PhD thesis, University of Cambridge.
MRC, I. Tolstikhin, G. Luque, N. Youngblut, R. Ley, B. Schölkopf. GeNet: Deep Representations for Metagenomics. Preprint. Code.
MRC, R. Turner, B. Schölkopf, J. Peters. Invariant Models For Causal Transfer Learning. JMLR 2018. Code.
G. Parascandolo, N. Kilbertus, MRC, B. Schölkopf. Learning Independent Causal Mechanisms. ICML 2018, NIPS workshops 2017.
N. Kilbertus, MRC, G. Parascandolo, M. Hardt, D. Janzing, B. Schölkopf. Avoiding Discrimination Through Causal Reasoning. NIPS 2017.
M. Bauer*, MRC*, B. Schölkopf, R. Turner. Discriminative k-shot Learning Using Probabilistic Models. NIPS workshops 2017.
MRC, M. Baroni, D. Lopez-Paz. Causal Discovery Using Proxy Variables. ICLR workshops 2017. Code.
mrc [at] lakera [dot] ai