From Classical to Unsupervised-Deep-Learning Methods for Solving Inverse Problems in Imaging.
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Given a state-of-the-art deep neural network classifier, we show the existence of a universal (image-agnostic) and very small perturbation vector that causes natural images to be misclassified with high probability. We propose a systematic algorithm for co ...
The effective reverse engineering of biochemical networks is one of the great challenges of systems biology. The contribution of this paper is two-fold: 1) We introduce a new method for reverse engineering genetic regulatory networks from gene expression d ...
A novel hybrid evolutionary neural network method to generate multiple spectrum-compatible artificial earthquake accelerograms (SCAEAs) is presented. Genetic algorithm is employed to optimize the weight values of networks. In order to improve the training ...
PyBrain is a versatile machine learning library for Python. Its goal is to provide flexible, easy-to-use yet still powerful algorithms for machine learning tasks, including a variety of predefined environments and benchmarks to test and compare algorithms. ...
We present an implementation and laboratory tests of a winner takes all (WTA) artificial neural network (NN) on two microcontrollers (μC) with the ARM Cortex M3 and the AVR cores. The prospective application of this device is in wireless body sensor networ ...
School of Engineering, The University of Waikato2010
The manual design of adaptive controllers for robotic systems that face unpredictable environmental changes is often challenging. There is thus a growing interest in the development of automatic design tools to assist control engineers. One of the most com ...
In this paper, an automatic synthesis methodology based on evolutionary computation is applied to evolve neural controllers for a homogeneous team of miniature autonomous mobile robots. Both feed-forward and recurrent neural networks can be evolved with fi ...
In this article we review several successful extensions to the standard Hidden-Markov-Model/Artificial Neural Network (HMM/ANN) hybrid, which have recently made important contributions to the field of noise robust automatic speech recognition. The first ex ...
Linear inverse problems with discrete data are equivalent to the estimation of the continuous-time input of a linear dynamical system from samples of its output. The solution obtained by means of regularization theory has the structure of a neural network ...
The solution of linear inverse problems obtained by means of regularization theory has the structure of a neural network similar to classical RBF networks. However, the basis functions depend in a nontrivial way on the specific linear operator to be invert ...