On Linear Interpolation in the Latent Space of Deep Generative Models

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Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

We obtain new Fourier interpolation and uniqueness results in all dimensions, extending methods and results by the first author and M. Sousa [11] and the second author [12]. We show that the only Schwartz function which, together with its Fourier transform ...

In several machine learning settings, the data of interest are well described by graphs. Examples include data pertaining to transportation networks or social networks. Further, biological data, such as proteins or molecules, lend themselves well to graph- ...

The task of discovering equivalent entities in knowledge graphs (KGs), so-called KG entity alignment, has drawn much attention to overcome the incompleteness problem of KGs. The majority of existing techniques learns the pointwise representations of entiti ...

Let K be a totally real number field of degree n >= 2. The inverse different of K gives rise to a lattice in Rn. We prove that the space of Schwartz Fourier eigenfunctions on R-n which vanish on the "component-wise square root" of this lattice, is infinite ...

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

This work introduces a diffusion model for molecule generation in 3D that is equivariant to Euclidean transformations. Our E(3) Equivariant Diffusion Model (EDM) learns to denoise a diffusion process with an equivariant network that jointly operates on bot ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

Fetal brain diffusion magnetic resonance images (MRI) are often acquired with a lower through-plane than in-plane resolution. This anisotropy is often overcome by classical upsampling methods such as linear or cubic interpolation. In this work, we employ a ...

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

Classic image-restoration algorithms use a variety of priors, either implicitly or explicitly. Their priors are hand-designed and their corresponding weights are heuristically assigned. Hence, deep learning methods often produce superior image restoration ...

Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

On Linear Interpolation in the Latent Space of Deep Generative Models

Chattez avec Graph Search

Dynamism in the context of views out: A literature review

Perturbed Fourier uniqueness and interpolation results in higher dimensions

Graph Representation Learning with Optimal Transport: Analysis and Applications

Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment

Fourier non-uniqueness sets from totally real number fields

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Equivariant Diffusion for Molecule Generation in 3D

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Through-Plane Super-Resolution With Autoencoders in Diffusion Magnetic Resonance Imaging of the Developing Human Brain

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit