7 papers
Flow Matching Calibration for Simulation-Based Inference under Model Misspecification
Pierre-Louis Ruhlmann, Michael Arbel, Florence Forbes +1
Simulation-based inference (SBI) is transforming experimental sciences by enabling parameter estimation in complex non-linear models from simulated data. A persistent challenge, ho…
: 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…
Semiparametric Efficient Bilevel Gradient Estimation
Fares El Khoury, Houssam Zenati, Nathan Kallus +2
Functional bilevel methods estimate a lower-level function and plug it into a hypergradient, but this plug-in gradient can retain first-order bias when the lower-level problem is l…
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…
Beyond MMSE: Enhancing PnP Restoration with ProxiMAP
Kenta Vert, Giacomo Meanti, Scott Pesme +2
Plug-and-Play (PnP) methods have become standard tools for solving imaging inverse problems by replacing the intractable maximum a posteriori (MAP) denoiser with the MMSE one. Whil…
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…