456 research outputs found
Life is a die
Life are consist of uncertainty and certainty. The most functional way for people to deal with life is to try their best for certainty and to accept uncertainty. However, due to the consistently changing environment and fast increasing uncertainty, people are more and more unlikely to deal with life and its uncertainty. This project, Life-is-a-die, will express the personal thought to deal with life and release worries and fear through a poetic video. In this video, the designed metaphors, poetic story, sound effects, text, 3d elements, motions, visuals, motion, and textures will play a vital role to help people understand and learn the whole theme
Linear isometric invariants of bounded domains
We introduce two new conditions for bounded domains, namely
-completeness and boundary blow down type, and show that, for two bounded
domains and that are -complete and not of boundary blow down
type, if there exists a linear isometry from to for
some real number with even integers, then and must
be holomorphically equivalent, where for a domain , denotes the
space of holomorphic functions on .Comment: 14pages, comments welcome
Subsampling-Based Modified Bayesian Information Criterion for Large-Scale Stochastic Block Models
Identifying the number of communities is a fundamental problem in community
detection, which has received increasing attention recently. However, rapid
advances in technology have led to the emergence of large-scale networks in
various disciplines, thereby making existing methods computationally
infeasible. To address this challenge, we propose a novel subsampling-based
modified Bayesian information criterion (SM-BIC) for identifying the number of
communities in a network generated via the stochastic block model and
degree-corrected stochastic block model. We first propose a node-pair
subsampling method to extract an informative subnetwork from the entire
network, and then we derive a purely data-driven criterion to identify the
number of communities for the subnetwork. In this way, the SM-BIC can identify
the number of communities based on the subsampled network instead of the entire
dataset. This leads to important computational advantages over existing
methods. We theoretically investigate the computational complexity and
identification consistency of the SM-BIC. Furthermore, the advantages of the
SM-BIC are demonstrated by extensive numerical studies
: Zero-shot Style Transfer via Attention Rearrangement
Despite the remarkable progress in image style transfer, formulating style in
the context of art is inherently subjective and challenging. In contrast to
existing learning/tuning methods, this study shows that vanilla diffusion
models can directly extract style information and seamlessly integrate the
generative prior into the content image without retraining. Specifically, we
adopt dual denoising paths to represent content/style references in latent
space and then guide the content image denoising process with style latent
codes. We further reveal that the cross-attention mechanism in latent diffusion
models tends to blend the content and style images, resulting in stylized
outputs that deviate from the original content image. To overcome this
limitation, we introduce a cross-attention rearrangement strategy. Through
theoretical analysis and experiments, we demonstrate the effectiveness and
superiority of the diffusion-based ero-shot tyle
ransfer via ttention earrangement,
Z-STAR
Approximation and extension of Hermitian metrics on holomorphic vector bundles over Stein manifolds
We show that a singular Hermitian metric on a holomorphic vector bundle over
a Stein manifold which is negative in the sense of Griffiths (resp. Nakano) can
be approximated by a sequence of smooth Hermitian metrics with the same
curvature negativity. We also show that a smooth Hermitian metric on a
holomorphic vector bundle over a Stein manifold restricted to a submanifold
which is negative in the sense of Griffiths (resp. Nakano) can be extended to
the whole bundle with the same curvature negativity.Comment: 10pages. Comments welcome
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