
Hyperbolic Distance Matrices
Hyperbolic space is a natural setting for mining and visualizing data wi...
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Learning Extremal Representations with Deep Archetypal Analysis
Archetypes are typical population representatives in an extremal sense, ...
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Regional Tree Regularization for Interpretability in Black Box Models
The lack of interpretability remains a barrier to the adoption of deep n...
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Control of Stochastic Quantum Dynamics with Differentiable Programming
Controlling stochastic dynamics of a quantum system is an indispensable ...
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Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
The lack of interpretability remains a key barrier to the adoption of de...
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Feedforward approximations to dynamic recurrent network architectures
Recurrent neural network architectures can have useful computational pro...
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Causal Compression
We propose a new method of discovering causal relationships in temporal ...
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Gaussian Process Morphable Models
Statistical shape models (SSMs) represent a class of shapes as a normal ...
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Entropy inference and the JamesStein estimator, with application to nonlinear gene association networks
We present a procedure for effective estimation of entropy and mutual in...
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Web Video in Numbers  An Analysis of WebVideo Metadata
Web video is often used as a source of data in various fields of study. ...
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Towards Adaptive Resilience in High Performance Computing
Failure rates in high performance computers rapidly increase due to the ...
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Off the Beaten Track: Using Deep Learning to Interpolate Between Music Genres
We describe a system based on deep learning that generates drum patterns...
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AirLab: Autograd Image Registration Laboratory
Medical image registration is an active research topic and forms a basis...
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Causal Deep Information Bottleneck
Estimating causal effects in the presence of latent confounding is a fre...
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OpenMP Loop Scheduling Revisited: Making a Case for More Schedules
In light of continued advances in loop scheduling, this work revisits th...
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Towards a MiniApp for Smoothed Particle Hydrodynamics at Exascale
The smoothed particle hydrodynamics (SPH) technique is a purely Lagrangi...
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Adaptive Planner Scheduling with Graph Neural Networks
Automated planning is one of the foundational areas of AI. Since a singl...
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Learning Features and Abstract Actions for Computing Generalized Plans
Generalized planning is concerned with the computation of plans that sol...
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Open Power System Data  Frictionless data for electricity system modelling
The quality of electricity system modelling heavily depends on the input...
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Detecting quantum speedup by quantum walk with convolutional neural networks
Quantum walks are at the heart of modern quantum technologies. They allo...
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Towards an AllPurpose ContentBased Multimedia Information Retrieval System
The growth of multimedia collections  in terms of size, heterogeneity, ...
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Tensor BSpline Numerical Methods for PDEs: a HighPerformance Alternative to FEM
Tensor Bspline methods are a highperformance alternative to solve part...
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Detection of Silent Data Corruptions in Smoothed Particle Hydrodynamics Simulations
Silent data corruptions (SDCs) hinder the correctness of longrunning sc...
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SPHEXA: Enhancing the Scalability of SPH codes Via an ExascaleReady SPH MiniApp
Numerical simulations of fluids in astrophysics and computational fluid ...
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ExponentialBinary StateSpace Search
Iterative deepening search is used in applications where the best cost b...
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A Closest Point Proposal for MCMCbased Probabilistic Surface Registration
In this paper, we propose a nonrigid surface registration algorithm tha...
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Optimizing for Interpretability in Deep Neural Networks with Tree Regularization
Deep models have advanced prediction in many domains, but their lack of ...
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3D Morphable Face Models – Past, Present and Future
In this paper, we provide a detailed survey of 3D Morphable Face Models ...
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HigherDimensional Potential Heuristics for Optimal Classical Planning
Potential heuristics for statespace search are defined as weighted sums...
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Neural networks and kernel ridge regression for excited states dynamics of CH_2NH_2^+: From singlestate to multistate representations and multiproperty machine learning mode
Excitedstate dynamics simulations are a powerful tool to investigate ph...
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Machine learning transfer efficiencies for noisy quantum walks
Quantum effects are known to provide an advantage in particle transfer a...
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The Variance of Causal Effect Estimators for Binary Vstructures
Adjusting for covariates is a well established method to estimate the to...
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A Smoothed Particle Hydrodynamics MiniApp for Exascale
The Smoothed Particles Hydrodynamics (SPH) is a particlebased, meshfree...
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Mapping Matters: Application Process Mapping on 3D Processor Topologies
Applications' performance is influenced by the mapping of processes to c...
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Adaptive spectral decompositions for inverse medium problems
Inverse medium problems involve the reconstruction of a spatially varyin...
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Geometry of Comparisons
Many data analysis problems can be cast as distance geometry problems in...
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Globally Injective ReLU Networks
We study injective ReLU neural networks. Injectivity plays an important ...
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Regulation conform DLToperable payment adapter based on trustless  justified trust combined generalized state channels
Open technologies, decentralized computation and intelligent application...
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Leading Digital SocioEconomy to Efficiency – A Primer on Tokenomics
Through the usage of cryptographically secure and digitally scarce token...
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3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies
Segmentation of distinct bones plays a crucial role in diagnosis, planni...
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To fit or not to fit: Modelbased Face Reconstruction and Occlusion Segmentation from Weak Supervision
3D face reconstruction from a single image is challenging due to its ill...
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SwarMS: SwarmComputations for Mobile Scenarios
Nowadays, most network systems are based on fixed and reliable infrastru...
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Tangle Centric Networking (TCN)
Today's Internet is heavily used for multimedia streaming from cloud bac...
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Universal Approximation Under Constraints is Possible with Transformers
Many practical problems need the output of a machine learning model to s...
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Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows
We analyze neural networks composed of bijective flows and injective exp...
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Neural Link Prediction with Walk Pooling
Graph neural networks achieve high accuracy in link prediction by jointl...
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Universität Basel
The University of Basel is the oldest university in Switzerland. As a researchstrong university, it offers students an attractive educational offer.