Zobrazeno 1 - 10
of 94 154
pro vyhledávání: '"Mira, A."'
In this paper, we aim to generate clean speech frame by frame from a live video stream and a noisy audio stream without relying on future inputs. To this end, we propose RT-LA-VocE, which completely re-designs every component of LA-VocE, a state-of-t
Externí odkaz:
http://arxiv.org/abs/2407.07825
Large Language Models trained on code corpora (code-LLMs) have demonstrated impressive performance in various coding assistance tasks. However, despite their increased size and training dataset, code-LLMs still have limitations such as suggesting cod
Externí odkaz:
http://arxiv.org/abs/2406.11930
Autor:
Varma, Mira, Baker, Oliver
This paper investigates the relationship between initial spatial anisotropy and final state momentum anisotropy in heavy ion collisions through the analysis of elliptic flow ($\nu_2$) as a function of transverse momentum ($p_T$). Building upon previo
Externí odkaz:
http://arxiv.org/abs/2406.10129
The European carbon market plays a pivotal role in the European Union's ambitious target of achieving carbon neutrality by 2050. Understanding the intricacies of factors influencing European Union Emission Trading System (EU ETS) market prices is par
Externí odkaz:
http://arxiv.org/abs/2406.05094
Autor:
Liu, Mira M., Saadat, Niloufar, Roth, Steven P., Niekrasz, Marek A., Giurcanu, Mihai, Carroll, Timothy J., Christoforidis, Gregory A.
In ischemic stroke, leptomeningeal collaterals can provide compensatory blood flow to tissue at risk despite an occlusion, and impact treatment response and infarct growth. The purpose of this work is to test the hypothesis that local perfusion with
Externí odkaz:
http://arxiv.org/abs/2406.04026
Linear algebra computations are foundational for neural networks and machine learning, often handled through arrays. While many functional programming languages feature lists and recursion, arrays in linear algebra demand constant-time access and bul
Externí odkaz:
http://arxiv.org/abs/2405.18242
Federated learning (FL) allows for collaborative model training across decentralized clients while preserving privacy by avoiding data sharing. However, current FL methods assume conditional independence between client models, limiting the use of pri
Externí odkaz:
http://arxiv.org/abs/2405.16055
Mixed-consistency programming models assist programmers in designing applications that provide high availability while still ensuring application-specific safety invariants. However, existing models often make specific system assumptions, such as bui
Externí odkaz:
http://arxiv.org/abs/2405.15578
Robust Bayesian analysis has been mainly devoted to detecting and measuring robustness to the prior distribution. Indeed, many contributions in the literature aim to define suitable classes of priors which allow the computation of variations of quant
Externí odkaz:
http://arxiv.org/abs/2405.15141
The Intrinsic Dimension (ID) is a key concept in unsupervised learning and feature selection, as it is a lower bound to the number of variables which are necessary to describe a system. However, in almost any real-world dataset the ID depends on the
Externí odkaz:
http://arxiv.org/abs/2405.15132