Lightweight Modular Staging and Embedded Compilers : Abstraction without Regret for High-Level High-Performance Programming

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As one of the major threats to women's health worldwide, breast cancer requires early diagnosis and accurate classification, since they are key to optimizing therapeutic interventions and ensuring precise prognosis. Recently, deep learning has demonstrated ...

Formally verifying the correctness of software is necessary to merit the trust people put in software systems. Currently, formal verification requires human effort to prove that a piece of code matches its specification and code changes to improve verifiab ...

Deploying energy-efficient deep neural networks on energy-constrained edge devices is an important research topic in both machine learning and circuit design communities. Both artificial neural networks (ANNs) and spiking neural networks (SNNs) have been p ...

Genes implicated in translation control have been associated with autism spectrum disorders (ASDs). However, some important genetic causes of autism, including the 16p11.2 microdeletion, bear no obvious connection to translation. Here, we use proteomics, g ...

Type inference in the presence of first-class or "impredicative" second-order polymorphism a la System F has been an active research area for several decades, with original works dating back to the end of the 80s. Yet, until now many basic problems remain ...

Now is an exciting time for the domain of Earth observation (EO), with a multitude of diverse sensors looking at the planet from satellites, airplanes or drones. The volume of imagery acquired is massive, and hold great potential for a variety of applicati ...

Many empirical studies have provided evidence for the emergence of algorithmic mechanisms (abilities) in the learning of language models, that lead to qualitative improvements in the model capabilities. Yet, a theoretical characterization of how such mecha ...

Type systems are a device for verifying properties of programs without running them. Many programming languages used in the industry have always had a type system, while others were initially created without a type system and later adopted one, when the ad ...

The thesis explores the issue of fairness in the real-time (RT) control of battery energy storage systems (BESSs) hosted in active distribution networks (ADNs) in the presence of uncertainties by proposing and experimentally validating appropriate control ...

Differences in acquisition protocols or hardware result in measurable changes in image characteristics. These differences affect distributional properties and can also affect the spatial and temporal characteristics of the images. Likewise, the distributio ...

FDTD/FEM simulations, strengthened by machine learning, achieve 95.44% optical absorption efficiency in TiO 2 /TiN plasmonic nanocavities for solar energy harvesting. ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

A metaprogrammer should be able to reason about the semantics of the generated code. Multi-stage programming introduced an elegant and powerful solution to this problem. It follows a semantically driven approach to code generation, where semantics are full ...

Sign Language conveys information through multiple channels composed of manual (handshape, hand movement) and non-manual (facial expression, mouthing, body posture) components. Sign language assessment involves giving granular feedback to a learner, in ter ...

Compilers assure that any produced optimized code is semantically equivalent to the original code. However, even "correct" compilers may introduce security bugs as security properties go beyond translation correctness. Security bugs introduced by such corr ...

MiMiC is a flexible and efficient framework for multiscale simulations in which different subsystems are treated by individual client programs. In this work, we present a new interface with OpenMM to be used as an MM client program and we demonstrate its e ...

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

Real-time bioaerosol monitoring is improving the quality of life for people affected by allergies, but it often relies on deep learning models which pose challenges for widespread adoption. These models are typically trained in a supervised fashion and req ...

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

Lightweight Modular Staging and Embedded Compilers : Abstraction without Regret for High-Level High-Performance Programming

Chattez avec Graph Search

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

Automated Formal Verification of Software Network Functions

Eflop: a Sparsity-aware Metric for Evaluating Computational Cost in Spiking and Non-spiking Neural Networks

The autism susceptibility kinase, TAOK2, phosphorylates eEF2 and modulates translation

When Subtyping Constraints Liberate A Novel Type Inference Approach for First-Class Polymorphism

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

A phase transition between positional and semantic learning in a solvable model of dot-product attention

Formal Foundations of Capture Tracking

Fair real-time control of energy storage systems in active distribution networks in the presence of uncertainties

Domain shift, domain adaptation, and generalization: A focus on MRI

Machine-learning-empowered FDTD/FEM simulations for predictive solar energy absorption in plasmonic metamaterial nanocavity arrays

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Scalable Metaprogramming in Scala 3

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Silent Bugs Matter: A Study of Compiler-Introduced Security Bugs

OpenMM–MiMiC Interface for Efficient and Flexible Multiscale Simulations

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Self-supervised and few-shot learning for robust bioaerosol monitoring

Dense Image-based Predictions for Comics Analysis

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology