Zobrazeno 1 - 10
of 14 429
pro vyhledávání: '"A Barbu"'
Autor:
Kansabanik, Rittwika, Barbu, Adrian
Feature selection is crucial for pinpointing relevant features in high-dimensional datasets, mitigating the 'curse of dimensionality,' and enhancing machine learning performance. Traditional feature selection methods for classification use data from
Externí odkaz:
http://arxiv.org/abs/2412.10128
Autor:
Barbu, Viorel
The mean-field game system is treated as an Euler Lagrange system corresponding to an optimal control problem governed by Fokker-Planck equation.
Externí odkaz:
http://arxiv.org/abs/2411.10301
Autor:
Wang, Christopher, Yaari, Adam Uri, Singh, Aaditya K, Subramaniam, Vighnesh, Rosenfarb, Dana, DeWitt, Jan, Misra, Pranav, Madsen, Joseph R., Stone, Scellig, Kreiman, Gabriel, Katz, Boris, Cases, Ignacio, Barbu, Andrei
We present the Brain Treebank, a large-scale dataset of electrophysiological neural responses, recorded from intracranial probes while 10 subjects watched one or more Hollywood movies. Subjects watched on average 2.6 Hollywood movies, for an average
Externí odkaz:
http://arxiv.org/abs/2411.08343
Autor:
Mayo, David, Wang, Christopher, Harbin, Asa, Alabdulkareem, Abdulrahman, Shaw, Albert Eaton, Katz, Boris, Barbu, Andrei
When evaluating stimuli reconstruction results it is tempting to assume that higher fidelity text and image generation is due to an improved understanding of the brain or more powerful signal extraction from neural recordings. However, in practice, n
Externí odkaz:
http://arxiv.org/abs/2411.02783
Autor:
Conwell, Colin, Hamblin, Christopher, Boccagno, Chelsea, Mayo, David, Cummings, Jesse, Isik, Leyla, Barbu, Andrei
When we experience a visual stimulus as beautiful, how much of that experience derives from perceptual computations we cannot describe versus conceptual knowledge we can readily translate into natural language? Disentangling perception from language
Externí odkaz:
http://arxiv.org/abs/2410.23603
Autor:
Domnich, Marharyta, Valja, Julius, Veski, Rasmus Moorits, Magnifico, Giacomo, Tulver, Kadi, Barbu, Eduard, Vicente, Raul
As machine learning models evolve, maintaining transparency demands more human-centric explainable AI techniques. Counterfactual explanations, with roots in human reasoning, identify the minimal input changes needed to obtain a given output and, henc
Externí odkaz:
http://arxiv.org/abs/2410.21131
Autor:
Subramaniam, Vighnesh, Mayo, David, Conwell, Colin, Poggio, Tomaso, Katz, Boris, Cheung, Brian, Barbu, Andrei
We demonstrate that architectures which traditionally are considered to be ill-suited for a task can be trained using inductive biases from another architecture. Networks are considered untrainable when they overfit, underfit, or converge to poor res
Externí odkaz:
http://arxiv.org/abs/2410.20035
Autor:
Kansabanik, Rittwika, Barbu, Adrian
This paper introduces a Video Quality Assessment (VQA) problem that has received little attention in the literature, called the latent resolution prediction problem. The problem arises when images or videos are upscaled from their native resolution a
Externí odkaz:
http://arxiv.org/abs/2410.13227
Autor:
Berceanu, Barbu Rudolf
We recall the fundamental theorem of J.F. Ritt, with a stress on the action of the affine group and canonical forms of complex polynomials. Then we give a complete presentation of the monoid $(\mathbb{C}\mbox{[X]},\circ)$. A list of decomposable poly
Externí odkaz:
http://arxiv.org/abs/2410.12447
Autor:
Barbu, Viorel
One proves the well-posedness in the Sobolev space H^{-1} of nonlinear Fokker-Planck equations with singular drifts.Applications to existence of strong solutions to McKean-Vlasov equations are given.
Externí odkaz:
http://arxiv.org/abs/2410.09822