
Automatic design of novel potential 3CL^pro and PL^pro inhibitors
With the goal of designing novel inhibitors for SARSCoV1 and SARSCoV...
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Learning to Detect Objects with a 1 Megapixel Event Camera
Event cameras encode visual information with high temporal precision, lo...
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Realtime Classification from Short EventCamera Streams using Inputfiltering Neural ODEs
Eventbased cameras are novel, efficient sensors inspired by the human v...
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Tractogram filtering of anatomically nonplausible fibers with geometric deep learning
Tractograms are virtual representations of the white matter fibers of th...
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Deep Graph Matching Consensus
This work presents a twostage neural architecture for learning and refi...
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InfiniteHorizon Differentiable Model Predictive Control
This paper proposes a differentiable linear quadratic Model Predictive C...
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No Representation without Transformation
We propose to extend Latent Variable Models with a simple idea: learn to...
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Safe Interactive ModelBased Learning
Control applications present hard operational constraints. A violation o...
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Accelerating Neural ODEs with Spectral Elements
This paper proposes the use of spectral element methods canuto_spectral_...
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Recurrent Neural Processes
We extend Neural Processes (NPs) to sequential data through Recurrent NP...
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Conditional Neural Style Transfer with PeerRegularized Feature Transform
This paper introduces a neural style transfer model to conditionally gen...
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Differentiable Iterative Surface Normal Estimation
This paper presents an endtoend differentiable algorithm for anisotrop...
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ReConvNet: Video Object Segmentation with SpatioTemporal Features Modulation
We introduce ReConvNet, a recurrent convolutional architecture for semi...
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PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
Deep learning systems have become ubiquitous in many aspects of our live...
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NAISNet: Stable Deep Networks from NonAutonomous Differential Equations
This paper introduces "NonAutonomous InputOutput Stable Network" (NAIS...
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Geometric deep learning on graphs and manifolds using mixture model CNNs
Deep learning has achieved a remarkable performance breakthrough in seve...
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Learning shape correspondence with anisotropic convolutional neural networks
Establishing correspondence between shapes is a fundamental problem in g...
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Geodesic convolutional neural networks on Riemannian manifolds
Feature descriptors play a crucial role in a wide range of geometry anal...
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Understanding Locally Competitive Networks
Recently proposed neural network activation functions such as rectified ...
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Deep Networks with Internal Selective Attention through Feedback Connections
Traditional convolutional neural networks (CNN) are stationary and feedf...
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Sparse similaritypreserving hashing
In recent years, a lot of attention has been devoted to efficient neares...
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Fast Image Scanning with Deep MaxPooling Convolutional Neural Networks
Deep Neural Networks now excel at image classification, detection and se...
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A Fast Learning Algorithm for Image Segmentation with MaxPooling Convolutional Networks
We present a fast algorithm for training MaxPooling Convolutional Networ...
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A Learning Framework for Morphological Operators using CounterHarmonic Mean
We present a novel framework for learning morphological operators using ...
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Object Recognition with MultiScale Pyramidal Pooling Networks
We present a MultiScale Pyramidal Pooling Network, featuring a novel py...
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Multimodal similaritypreserving hashing
We introduce an efficient computational framework for hashing data belon...
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Descriptor learning for omnidirectional image matching
Feature matching in omnidirectional vision systems is a challenging prob...
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HighPerformance Neural Networks for Visual Object Classification
We present a fast, fully parameterizable GPU implementation of Convoluti...
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Jonathan Masci
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PostDoctoral Researcher at Università della Svizzera Italiana