Results 11 to 20 of about 5,235,033 (372)
ClusterGAN : Latent Space Clustering in Generative Adversarial Networks [PDF]
AAAI Conference on Artificial Intelligence, 2019 Generative Adversarial networks (GANs) have obtained remarkable success in many unsupervised learning tasks and unarguably, clustering is an important unsupervised learning problem.
Asnani, Himanshu +3 more
core +2 more sources
Pseudospline interpolation for space curves [PDF]
Mathematics of Computation, 1976 A method for interpolating a curve through points in space is described. It is the direct analogue of Fowler-Wilson or pseudospline interpolation for plane curves in that local coordinate systems, cubic polynomials of suitable parameters, and mildly nonlinear equations are used to obtain a continuous interpolating curve with continuous tangent and ...
Donald Thomas
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Monotonicity properties of interpolation spaces [PDF]
Arkiv för Matematik, 1976 For any interpolation pair (A 0 A 1), Peetre’sK-functional is defined by: $$K\left( {t,a;A_0 ,A_1 } \right) = \mathop {\inf }\limits_{a = a_0 + a_1 } \left( {\left\| {a_0 } \right\|_{A_0 } + t\left\| {a_1 } \right\|_{A_1 ...
Michael Ćwikel
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LDMVFI: Video Frame Interpolation with Latent Diffusion Models [PDF]
AAAI Conference on Artificial Intelligence, 2023 Existing works on video frame interpolation (VFI) mostly employ deep neural networks that are trained by minimizing the L1, L2, or deep feature space distance (e.g. VGG loss) between their outputs and ground-truth frames. However, recent works have shown
Duolikun Danier +2 more
semanticscholar +1 more source
Temporal Interpolation is all You Need for Dynamic Neural Radiance Fields [PDF]
Computer Vision and Pattern Recognition, 2023 Temporal interpolation often plays a crucial role to learn meaningful representations in dynamic scenes. In this paper, we propose a novel method to train spatiotemporal neural radiance fields of dynamic scenes based on temporal interpolation of feature ...
Sungheon Park +5 more
semanticscholar +1 more source
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 This paper presents MixText, a semi-supervised learning method for text classification, which uses our newly designed data augmentation method called TMix.
Jiaao Chen, Zichao Yang, Diyi Yang
semanticscholar +1 more source
Video Frame Interpolation Transformer [PDF]
Computer Vision and Pattern Recognition, 2021 Existing methods for video interpolation heavily rely on deep convolution neural networks, and thus suffer from their intrinsic limitations, such as content-agnostic kernel weights and restricted receptive field.
Zhihao Shi +4 more
semanticscholar +1 more source
The positivity of the differential operator generated by hyperbolic system of equations [PDF]
E-Journal of Analysis and Applied Mathematics, 2023 In the present paper, the initial value problem for the hyperbolic system of equations with nonlocal boundary conditions is investigated. The positivity of the space operator generated by the given problem in interpolation spaces is established.
Rahat Prenov
doaj +1 more source
Fractal and Fractional, 2023 In this paper, we studied the Hölder regularities of solutions to an abstract fractional differential equation, which is regarded as an abstract version of fractional Rayleigh–Stokes problems, rising up to describing a non-Newtonian fluid with a Riemann ...
Jiawei He, Guangmeng Wu
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FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space [PDF]
Computer Vision and Pattern Recognition, 2021 Federated learning allows distributed medical institutions to collaboratively learn a shared prediction model with privacy protection. While at clinical deployment, the models trained in federated learning can still suffer from performance drop when ...
Quande Liu +4 more
semanticscholar +1 more source