Centre Inria de Saclay

Slow Frontal Spindle Activity and Declarative Memory Retention During Daytime Naps

ABSTRACT Memory consolidation refers to how newly encoded memories are strengthened and retained over time, and ample evidence indicates that sleep supports this process for both procedural and declarative memories. Although sleep spindles during non‐rapid eye movement (NREM) sle...

What is the Role of Small Models in the LLM Era: A Survey

Abstract Large Language Models (LLMs) have demonstrated remarkable capabilities in various reasoning tasks, which leads to the development of increasingly large models. However, scaling up model sizes results in significantly higher computational costs and energy consumption, whi...

Unsupervised deep learning for limited-angle STEM-EDX tomography: application to 3D chemical analysis of phase-change memory devices

Abstract Energy-dispersive X-ray (EDX) tomography in scanning transmission electron microscopy (STEM) enables three-dimensional elemental mapping at the nanoscale. However, its application remains challenging when sample geometry severely restricts the accessible tilt range, and...

Efficient Hamiltonian, structure and trace distance learning of Gaussian states

Abstract When learning descriptions of many-body quantum systems, assuming locality of interactions can dramatically reduce the required number of observations and computational time compared to unstructured approaches. In this work, we uncover an infinite-dimensional instance of...

Continuous logistic Gaussian random measure fields for spatial distributional modelling

Abstract We study Spatial Logistic Gaussian Process (SLGP) models for non-parametric estimation of probability density fields using scattered samples of heterogeneous sizes. SLGPs are examined from the perspective of random measures and their densities, investigating the relation...

Learning aligned EEG representations with subject-specific encoders

Cross-subject EEG decoding promises more training data, but it also exposes neural networks to strong inter-subject distribution shifts. We study whether task supervision and architecture alone can learn subject-aligned representations. We replace a shared EEG encoder with subjec...

Bias in Genome-Wide Association Test Statistics Due to Omitted Interactions

Abstract Over the past two decades, genome-wide association studies (GWAS) enabled the discovery of thousands of variants associated with many complex human traits. However, conventional GWAS are still widely performed with linear models with the assumption that the genetic effec...

Misquoted No More: Securely Extracting F* Programs with IO

Shallow embeddings that use monads to represent effects are popular in proof-oriented languages because they are convenient for formal verification. Once shallowly embedded programs are verified, they are often extracted to mainstream languages like OCaml or C and linked into lar...

Confluence Techniques for Dependent Type Theory with Typed Conversion

In the meta-theoretic study of dependent type theory, confluence techniques are powerful tools for establishing the properties required when proving correctness of implementations. Unfortunately, such techniques have historically mostly been studied for type theories with untyped...

Experimental Investigation of Pressure Influence On A Swirled Stabilized Premixed Hydrogen-Air Flame For Aeronautical Applications Using Optical Diagnostics

Abstract Reducing carbon footprint of the aviation sector is essential for its sustainability. A promising solution for short-to-medium-haul flights is to replace kerosene with hydrogen combustion. This switch leads to significant changes in the architecture of the combustion cha...