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cs.LG2026
: Transformer-based inference from interaction maps
Eloïse Touron, Pedro L. C. Rodrigues, Julyan Arbel +2
Inference from interaction maps, such as centromere identification from genome-wide chromosome conformation capture techniques -- notably Hi-C -- can be formulated as a generic inv…
cs.LG2026
PEIRA: Learning Predictive Encoders through Inter-View Regressor Alignment
Michael Arbel, Basile Terver, Jean Ponce
Non-contrastive self-supervised learning (SSL) is an effective framework for predictive representation learning, but popular (and in practice effective) methods such as SimSiam, BY…
cs.LG2026
EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Networks
Michael Arbel, David Salinas, Frank Hutter
Recent foundational models for tabular data, such as TabPFN, excel at adapting to new tasks via in-context learning, but remain constrained to a fixed, pre-defined number of target…