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02/04/2023
Multi-Source Diffusion Models for Simultaneous Music Generation and Separation
In this work, we define a diffusion-based generative model capable of bo...
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01/09/2023
Latent Autoregressive Source Separation
Autoregressive models have achieved impressive results over a wide range...
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05/30/2022
Harnessing spectral representations for subgraph alignment
With the rise and advent of graph learning techniques, graph data has be...
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04/01/2022
Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications
Graphs are a powerful tool for representing and analyzing unstructured, ...
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02/03/2022
Bending Graphs: Hierarchical Shape Matching using Gated Optimal Transport
Shape matching has been a long-studied problem for the computer graphics...
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12/14/2021
Graph Kernel Neural Networks
The convolution operator at the core of many modern neural architectures...
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10/11/2021
Unsupervised Source Separation via Bayesian Inference in the Latent Domain
State of the art audio source separation models rely on supervised data-...
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06/25/2021
Shape registration in the time of transformers
In this paper, we propose a transformer-based procedure for the efficien...
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04/07/2021
Universal Spectral Adversarial Attacks for Deformable Shapes
Machine learning models are known to be vulnerable to adversarial attack...
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03/31/2021
Spectral Unions of Partial Deformable 3D Shapes
Spectral geometric methods have brought revolutionary changes to the fie...
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03/02/2021
Learning disentangled representations via product manifold projection
We propose a novel approach to disentangle the generative factors of var...
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03/27/2020
LIMP: Learning Latent Shape Representations with Metric Preservation Priors
In this paper, we advocate the adoption of metric preservation as a powe...
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03/27/2020
Latent Patient Network Learning for Automatic Diagnosis
Recently, Graph Convolutional Networks (GCNs) has proven to be a powerfu...
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02/11/2020
Differentiable Graph Module (DGM) Graph Convolutional Networks
Graph deep learning has recently emerged as a powerful ML concept allowi...
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11/28/2018
Isospectralization, or how to hear shape, style, and correspondence
The question whether one can recover the shape of a geometric object fro...
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06/17/2015