Learning Multimodal Temporal Representation for Dubbing Detection in Broadcast Media

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Given a sequence of functions

f_1,\ldots,f_n

with

f_i:\mathcal{D}\mapsto \mathbb{R}

, finite-sum minimization seeks a point

{x}^\star \in \mathcal{D}

minimizing

\sum_{j=1}^nf_j(x)/n

. In this work, we propose a key twist into the finite-sum minimizat ...

In this paper, we propose a reduced-order modeling strategy for two-way Dirichlet-Neumann parametric coupled problems solved with domain-decomposition (DD) sub-structuring methods. We split the original coupled differential problem into two sub-problems wi ...

When arranged in a crossbar configuration, resistive memory devices can be used to execute Matrix-Vector Multiplications (MVMs), the most dominant operation of many Machine Learning (ML) algorithms, in constant time complexity. Nonetheless, when performing ...

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

The process of protein aggregation, central to neurodegenerative diseases like Huntington’s, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease ...

Electrical stimulation of the visual nervous system could improve the quality of life of patients affected by acquired blindness by restoring some visual sensations, but requires careful optimization of stimulation parameters to produce useful perceptions. ...

Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

The invention relates to methods for the preparation of method of preparation of Tau aggregates, including fibrils, fibrillar species, soluble and insoluble oligomeric species, new Tau aggregates and uses thereof. The invention further relates to the uses ...

Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeability is no ...

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

Aim: Adolescents born very preterm (VPT;

Topographical disorientation refers to the selective inability to orient oneself in familiar surroundings. However, to date its neural correlates remain poorly understood. Here we use quantitative lesion analysis and a lesion network mapping approach in or ...

Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that theoretical resul ...

The temporal variability of the thalamus in functional networks may provide valuable insights into the pathophysiology of schizophrenia. To address the complexity of the role of the thalamic nuclei in psychosis, we introduced micro-co-activation patterns ( ...

In the last few years, stroke ranked as the second most common cause of death and is the third most significant condition affecting disability-adjusted life years (DALYs) worldwide. Being the most prevalent and quality of life impacting post-stroke symptom ...

When two objects slide against each other, wear and friction occur at their interface. The accumulation of wear forms what is commonly referred to as a ``third-body''. Understanding third-body evolution has significant applications in industry, where contr ...

In an era where portable electronic devices are indispensable for a wide range of activities, the need for displays that provide both long-lasting battery life and excellent visibility in different lighting conditions is increasingly important. Emissive di ...

Efficient sampling and approximation of Boltzmann distributions involving large sets of binary variables, or spins, are pivotal in diverse scientific fields even beyond physics. Recent advances in generative neural networks have significantly impacted this ...

Learning Multimodal Temporal Representation for Dubbing Detection in Broadcast Media

Chattez avec Graph Search

Efficient Continual Finite-Sum Minimization

A Reduced Order Model for Domain Decompositions with Non-conforming Interfaces

LIONHEART: A Layer-based Mapping Framework for Heterogeneous Systems with Analog In-Memory Computing Tiles

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Residual-based attention in physics-informed neural networks

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Method of preparation of amyloidogenic protein aggregates and uses thereof

Bulk measurement of membrane permeability for random cyclic peptides in living cells to guide drug development

Iterative removal of sources to model the turbulent electromotive force

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Impact of a mindfulness-based intervention on neurobehavioral functioning and its association with large-scale brain networks in preterm young adolescents

The neural correlates of topographical disorientation-a lesion analysis study

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Thalamic contributions to psychosis susceptibility: Evidence from co-activation patterns accounting for intra-seed spatial variability (μCAPs)

Probing and modulating inter-areal coupling in the cortical visual motion processing pathway with non-invasive brain stimulation

Modeling friction and wear using an adaptive discrete-continuum coupling

MEMS-based Tunable Metasurface for Reflective Display Applications

Sparse autoregressive neural networks for classical spin systems