research
∙
07/31/2023
Camoscio: an Italian Instruction-tuned LLaMA
In recent years Large Language Models (LLMs) have increased the state of...
share
research
∙
07/03/2023
Vector Quantile Regression on Manifolds
Quantile regression (QR) is a statistical tool for distribution-free est...
research
∙
06/26/2023
Fauno: The Italian Large Language Model that will leave you senza parole!
This paper presents Fauno, the first and largest open-source Italian con...
research
∙
05/17/2023
Accelerating Transformer Inference for Translation via Parallel Decoding
Autoregressive decoding limits the efficiency of transformers for Machin...
research
∙
05/16/2023
Massive Uniform Mesh Decimation via a Fast Intrinsic Delaunay Triangulation
Triangular meshes are still today the data structure at the main foundat...
research
∙
05/02/2023
Multimodal Neural Databases
The rise in loosely-structured data available through text, images, and ...
research
∙
04/17/2023
Leveraging sparse and shared feature activations for disentangled representation learning
Recovering the latent factors of variation of high dimensional data has ...
research
∙
03/17/2023
Fluid Dynamics Network: Topology-Agnostic 4D Reconstruction via Fluid Dynamics Priors
Representing 3D surfaces as level sets of continuous functions over ℝ^3 ...
research
∙
03/01/2023
Bootstrapping Parallel Anchors for Relative Representations
The use of relative representations for latent embeddings has shown pote...
research
∙
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...
research
∙
01/09/2023
Latent Autoregressive Source Separation
Autoregressive models have achieved impressive results over a wide range...
research
∙
01/09/2023
CaSpeR: Latent Spectral Regularization for Continual Learning
While biological intelligence grows organically as new knowledge is gath...
research
∙
11/26/2022
Reduced Representation of Deformation Fields for Effective Non-rigid Shape Matching
In this work we present a novel approach for computing correspondences b...
research
∙
10/04/2022
ASIF: Coupled Data Turns Unimodal Models to Multimodal Without Training
Aligning the visual and language spaces requires to train deep neural ne...
research
∙
09/30/2022
Relative representations enable zero-shot latent space communication
Neural networks embed the geometric structure of a data manifold lying i...
research
∙
09/20/2022
Sparse Vicious Attacks on Graph Neural Networks
Graph Neural Networks (GNNs) have proven to be successful in several pre...
research
∙
06/22/2022
KiloNeuS: Implicit Neural Representations with Real-Time Global Illumination
The latest trends in inverse rendering techniques for reconstruction use...
research
∙
06/08/2022
Metric Based Few-Shot Graph Classification
Many modern deep-learning techniques do not work without enormous datase...
research
∙
03/20/2022
3D Human Pose Estimation Using Möbius Graph Convolutional Networks
3D human pose estimation is fundamental to understanding human behavior....
research
∙
01/25/2022
Explanatory Learning: Beyond Empiricism in Neural Networks
We introduce Explanatory Learning (EL), a framework to let machines use ...
research
∙
01/13/2022
Fish sounds: towards the evaluation of marine acoustic biodiversity through data-driven audio source separation
The marine ecosystem is changing at an alarming rate, exhibiting biodive...
research
∙
12/14/2021
Graph Kernel Neural Networks
The convolution operator at the core of many modern neural architectures...
research
∙
12/14/2021
Why you should learn functional basis
Efficient and practical representation of geometric data is a ubiquitous...
research
∙
10/25/2021
Efficiently Parallelizable Strassen-Based Multiplication of a Matrix by its Transpose
The multiplication of a matrix by its transpose, A^T A, appears as an in...
research
∙
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-...
research
∙
08/04/2021
Learning to generate shape from global-local spectra
In this work, we present a new learning-based pipeline for the generatio...
research
∙
06/25/2021
Shape registration in the time of transformers
In this paper, we propose a transformer-based procedure for the efficien...
research
∙
04/07/2021
Universal Spectral Adversarial Attacks for Deformable Shapes
Machine learning models are known to be vulnerable to adversarial attack...
research
∙
03/31/2021
Spectral Unions of Partial Deformable 3D Shapes
Spectral geometric methods have brought revolutionary changes to the fie...
research
∙
03/02/2021
Learning disentangled representations via product manifold projection
We propose a novel approach to disentangle the generative factors of var...
research
∙
11/26/2020
Non-Rigid Puzzles
Shape correspondence is a fundamental problem in computer graphics and v...
research
∙
09/19/2020
High-Resolution Augmentation for Automatic Template-Based Matching of Human Models
We propose a new approach for 3D shape matching of deformable human shap...
research
∙
09/07/2020
Nonlinear Spectral Geometry Processing via the TV Transform
We introduce a novel computational framework for digital geometry proces...
research
∙
05/28/2020
Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification
Computer-aided diagnosis (CAD) is becoming a prominent approach to assis...
research
∙
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...
research
∙
03/14/2020
Instant recovery of shape from spectrum via latent space connections
We introduce the first learning-based method for recovering shapes from ...
research
∙
01/27/2020
The Whole Is Greater Than the Sum of Its Nonrigid Parts
According to Aristotle, a philosopher in Ancient Greece, "the whole is g...
research
∙
06/14/2019
Correspondence-Free Region Localization for Partial Shape Similarity via Hamiltonian Spectrum Alignment
We consider the problem of localizing relevant subsets of non-rigid geom...
research
∙
04/16/2019
ZoomOut: Spectral Upsampling for Efficient Shape Correspondence
We present a simple and efficient method for refining maps or correspond...
research
∙
12/06/2018
Self-supervised Learning of Dense Shape Correspondence
We introduce the first completely unsupervised correspondence learning a...
research
∙
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...
research
∙
09/28/2018
Functional Maps Representation on Product Manifolds
We consider the tasks of representing, analyzing and manipulating maps b...
research
∙
07/27/2018
FARM: Functional Automatic Registration Method for 3D Human Bodies
We introduce a new method for non-rigid registration of 3D human shapes....
research
∙
07/25/2017
Efficient Deformable Shape Correspondence via Kernel Matching
We present a method to match three dimensional shapes under non-isometri...
research
∙
07/09/2017
Localized Manifold Harmonics for Spectral Shape Analysis
The use of Laplacian eigenfunctions is ubiquitous in a wide range of com...
research
∙
01/03/2017
Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space
Many algorithms for the computation of correspondences between deformabl...
research
∙
11/25/2016
Geometric deep learning on graphs and manifolds using mixture model CNNs
Deep learning has achieved a remarkable performance breakthrough in seve...
research
∙
07/12/2016
Bayesian Inference of Bijective Non-Rigid Shape Correspondence
Many algorithms for the computation of correspondences between deformabl...
research
∙
05/20/2016
Learning shape correspondence with anisotropic convolutional neural networks
Establishing correspondence between shapes is a fundamental problem in g...
research
∙
01/22/2016
