Jonathan Masci

research

∙ 01/19/2022

Generative Models for Periodicity Detection in Noisy Signals

We introduce a new periodicity detection algorithm for binary time serie...

Ezekiel Barnett, et al. ∙

research

∙ 01/28/2021

Automatic design of novel potential 3CL^pro and PL^pro inhibitors

With the goal of designing novel inhibitors for SARS-CoV-1 and SARS-CoV-...

Timothy Atkinson, et al. ∙

research

∙ 09/28/2020

Learning to Detect Objects with a 1 Megapixel Event Camera

Event cameras encode visual information with high temporal precision, lo...

Etienne Perot, et al. ∙

research

∙ 04/07/2020

Real-time Classification from Short Event-Camera Streams using Input-filtering Neural ODEs

Event-based cameras are novel, efficient sensors inspired by the human v...

Giorgio Giannone, et al. ∙

research

∙ 03/24/2020

Tractogram filtering of anatomically non-plausible fibers with geometric deep learning

Tractograms are virtual representations of the white matter fibers of th...

Pietro Astolfi, et al. ∙

research

∙ 01/27/2020

Deep Graph Matching Consensus

This work presents a two-stage neural architecture for learning and refi...

Matthias Fey, et al. ∙

research

∙ 01/07/2020

Infinite-Horizon Differentiable Model Predictive Control

This paper proposes a differentiable linear quadratic Model Predictive C...

Sebastian East, et al. ∙

research

∙ 12/09/2019

No Representation without Transformation

We propose to extend Latent Variable Models with a simple idea: learn to...

Giorgio Giannone, et al. ∙

research

∙ 11/15/2019

Safe Interactive Model-Based Learning

Control applications present hard operational constraints. A violation o...

Marco Gallieri, et al. ∙

research

∙ 06/17/2019

Accelerating Neural ODEs with Spectral Elements

This paper proposes the use of spectral element methods canuto_spectral_...

Alessio Quaglino, et al. ∙

research

∙ 06/13/2019

Recurrent Neural Processes

We extend Neural Processes (NPs) to sequential data through Recurrent NP...

Timon Willi, et al. ∙

research

∙ 06/07/2019

Conditional Neural Style Transfer with Peer-Regularized Feature Transform

This paper introduces a neural style transfer model to conditionally gen...

Jan Svoboda, et al. ∙

research

∙ 04/15/2019

Differentiable Iterative Surface Normal Estimation

This paper presents an end-to-end differentiable algorithm for anisotrop...

Jan Eric Lenssen, et al. ∙

research

∙ 06/14/2018

ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation

We introduce ReConvNet, a recurrent convolutional architecture for semi-...

Francesco Lattari, et al. ∙

research

∙ 05/31/2018

PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks

Deep learning systems have become ubiquitous in many aspects of our live...

Jan Svoboda, et al. ∙

research

∙ 04/19/2018

NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations

This paper introduces "Non-Autonomous Input-Output Stable Network" (NAIS...

Marco Ciccone, et al. ∙

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...

Federico Monti, et al. ∙

research

∙ 05/20/2016

Learning shape correspondence with anisotropic convolutional neural networks

Establishing correspondence between shapes is a fundamental problem in g...

Davide Boscaini, et al. ∙

research

∙ 01/26/2015

Geodesic convolutional neural networks on Riemannian manifolds

Feature descriptors play a crucial role in a wide range of geometry anal...

Jonathan Masci, et al. ∙

research

∙ 10/05/2014

Understanding Locally Competitive Networks

Recently proposed neural network activation functions such as rectified ...

Rupesh Kumar Srivastava, et al. ∙

research

∙ 07/11/2014

Deep Networks with Internal Selective Attention through Feedback Connections

Traditional convolutional neural networks (CNN) are stationary and feedf...

Marijn Stollenga, et al. ∙

research

∙ 12/19/2013

Sparse similarity-preserving hashing

In recent years, a lot of attention has been devoted to efficient neares...

Jonathan Masci, et al. ∙

research

∙ 02/07/2013

Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks

Deep Neural Networks now excel at image classification, detection and se...

Alessandro Giusti, et al. ∙

research

∙ 02/07/2013

A Fast Learning Algorithm for Image Segmentation with Max-Pooling Convolutional Networks

We present a fast algorithm for training MaxPooling Convolutional Networ...

Jonathan Masci, et al. ∙

research

∙ 12/11/2012

A Learning Framework for Morphological Operators using Counter-Harmonic Mean

We present a novel framework for learning morphological operators using ...

Jonathan Masci, et al. ∙

research

∙ 07/07/2012

Object Recognition with Multi-Scale Pyramidal Pooling Networks

We present a Multi-Scale Pyramidal Pooling Network, featuring a novel py...

Jonathan Masci, et al. ∙

research

∙ 07/06/2012

Multimodal similarity-preserving hashing

We introduce an efficient computational framework for hashing data belon...

Jonathan Masci, et al. ∙

research

∙ 12/29/2011

Descriptor learning for omnidirectional image matching

Feature matching in omnidirectional vision systems is a challenging prob...

Jonathan Masci, et al. ∙

research

∙ 02/01/2011

High-Performance Neural Networks for Visual Object Classification

We present a fast, fully parameterizable GPU implementation of Convoluti...

Dan C. Cireşan, et al. ∙

Jonathan Masci

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