Simulation-Driven Approach for Business Rules Discovery

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The recent introduction of high entropy alloys presents an exciting opportunity for novel material performance, offering extensive possibilities for tailoring material properties. Dislocation mechanisms in these alloys must be fully understood since they 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 ...

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

The collimation system of the Future Circular Collider, operating with leptons (FCC-ee), must protect not only the experiments against backgrounds, but also the machine itself from beam losses. With a 17.8 MJ stored energy of the electron and positron beam ...

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 ...

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive ...

Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...

Introduced to enable a wider use of Earth Observation images using natural language, Remote Sensing Visual Question Answering (RSVQA) remains a challenging task, in particular for questions related to counting. To address this specific challenge, we propos ...

Recent transformer language models achieve outstanding results in many natural language processing (NLP) tasks. However, their enormous size often makes them impractical on memory-constrained devices, requiring practitioners to compress them to smaller net ...

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

The success of self-supervised learning in computer vision and natural language processing has motivated pretraining methods on tabular data. However, most existing tabular self-supervised learning models fail to leverage information across multiple data t ...

Neural machine translation (MT) and text generation have recently reached very high levels of quality. However, both areas share a problem: in order to reach these levels, they require massive amounts of data. When this is not present, they lack generaliza ...

Nonlinear optical frequency conversion is of fundamental importance in photonics and underpins countless of its applications: Sum- and difference-frequency generation in media with quadratic nonlinearity permits reaching otherwise inaccessible wavelength r ...

Polymer brushes have been theoretically described, their behavior under diverse conditions has been modeled, and their preparation via surface-initiated polymerizations (SIPs) has been progressively refined. However, despite three decades of research endea ...

In recent years, the use of chatbots in education has been driven by advances in natural language processing and the increasing availability of digital education platforms. Although the added value of educational chatbots appears promising, researchers hav ...

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 ...

Recent successes in deep learning for vision and natural language processing are attributed to larger models but come with energy consumption and scalability issues. Current training of digital deep-learning models primarily relies on backpropagation that ...

Simulation-Driven Approach for Business Rules Discovery

Chattez avec Graph Search

Effects of Rate-dependent Plasticity on Residual Stresses in Additive Manufacturing of Complex Alloys

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

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Social-Transmotion: Promptable Human Trajectory Prediction

Collimation simulations for the FCC-ee

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

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Transformer Models for Vision

Text Representation Learning for Low Cost Natural Language Understanding

Multi-task prompt-RSVQA to explicitly count objects on aerial images

Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models

Modeling Structured Data in Attention-based Models

XTab: Cross-table Pretraining for Tabular Transformers

Regularization Techniques for Low-Resource Machine Translation

Simulating supercontinua from mixed and cascaded nonlinearities

Opportunities, Challenges, and Pitfalls in Making, Characterizing, and Understanding Polymer Brushes

Harnessing Rule-Based Chatbots to Support Teaching Python Programming Best Practices

Dense Image-based Predictions for Comics Analysis

Backpropagation-free training of deep physical neural networks