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Efficient Subspace Search in Data Streams
EdouardFouché, FlorianKalinke, KlemensBöhm....
Published date-11/13/2020
OutlierDetection
In the real world, data streams are ubiquitous -- think of network traffic or sensor data. Mining patterns, e.g., outliers or clusters, from such data must take place in real …
Diffusion models for Handwriting Generation
TroyLuhman, EricLuhman....
Published date-11/13/2020
Handwritinggeneration
In this paper, we propose a diffusion probabilistic model for handwriting generation. Diffusion models are a class of generative models where samples start from Gaussian noise and are gradually denoised …
Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning
XuehuiWang, QingWang, YuzhiZhao....
Published date-11/13/2020
ImageSuper-Resolution, SuperResolution, Super-Resolution
Despite convolutional network-based methods have boosted the performance of single image super-resolution (SISR), the huge computation costs restrict their practical applicability. In this paper, we develop a computation efficient yet …
SHAD3S: A model to Sketch, Shade and Shadow
RaghavB.Venkataramaiyer, AbhishekJoshi, SaishaNarang....
Published date-11/13/2020
Hatching is a common method used by artists to accentuate the third dimension of a sketch, and to illuminate the scene. Our system SHAD3S attempts to compete with a human …
A grammar compressor for collections of reads with applications to the construction of the BWT
DiegoDíaz-Domínguez, GonzaloNavarro....
Published date-11/13/2020
We describe a grammar for DNA sequencing reads from which we can compute the BWT directly. Our motivation is to perform in succinct space genomic analyses that require complex string …
Better, Faster Fermionic Neural Networks
JamesS.Spencer, DavidPfau, AleksandarBotev....
Published date-11/13/2020
The Fermionic Neural Network (FermiNet) is a recently-developed neural network architecture that can be used as a wavefunction Ansatz for many-electron systems, and has already demonstrated high accuracy on small …