Concept

Boltzmann machine

Related publications (109)

Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements

Wulfram Gerstner, Tim Vogels, Guillaume Hennequin

Populations of neurons in motor cortex engage in complex transient dynamics of large amplitude during the execution of limb movements. Traditional network models with stochastically assigned synapses cannot reproduce this behavior. Here we introduce a clas ...

Cell Press2014

Weakly Supervised Object Segmentation with 004 dwaeConvolutional Neural Networks

Ronan Collobert, Pedro Henrique Oliveira Pinheiro

Can a machine learn how to segment different objects in real world images without having any prior knowledge about the delineation of the classes? In this paper, we demonstrate that this task is indeed possible. We address the problem by training a Convolu ...

Idiap2014

Learning, Inference, and Replay of Hidden State Sequences in Recurrent Spiking Neural Networks

Dane Sterling Corneil, Emre Neftci

Learning to recognize, predict, and generate spatio-temporal patterns and sequences of spikes is a key feature of nervous systems, and essential for solving basic tasks like localization and navigation. How this can be done by a spiking network, however, r ...

2014

Parallel retrieval of correlated patterns: From Hopfield networks to Boltzmann machines

Andrea De Antoni

In this work, we first revise some extensions of the standard Hopfield model in the low storage limit, namely the correlated attractor case and the multitasking case recently introduced by the authors. The former case is based on a modification of the Hebb ...

Elsevier2013

Robust triphone mapping for acoustic modeling

Hervé Bourlard, Milos Cernak, David Imseng

In this paper we revisit the recently proposed triphone mapping as an alternative to decision tree state clustering. We generalize triphone mapping to Kullback-Leibler based hidden Markov models for acoustic modeling and propose a modified training procedu ...

Idiap2013

Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone

Joao Emanuel Felipe Gerhard

Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired re ...

Public Library of Science2013

Shared control of a robot using EEG-based feedback signals

Inaki Asier Iturrate Gil

In the last years there has been an increasing interest on using human feedback during robot operation to incorporate non-expert human expertise while learning complex tasks. Most work has considered reinforcement learning frameworks were human feedback, p ...

2013

Active Learning: Any Value for Classification of Remotely Sensed Data?

Devis Tuia

Active learning, which has a strong impact on processing data prior to the classification phase, is an active research area within the machine learning community, and is now being extended for remote sensing applications. To be effective, classification mu ...

2013

Robust triphone mapping for acoustic modeling

Hervé Bourlard, Milos Cernak, David Imseng

2012

Computational Methods For Structured Sparse Component Analysis of Convolutive Speech Mixtures

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei

We cast the under-determined convolutive speech separation as sparse approximation of the spatial spectra of the mixing sources. In this framework we compare and contrast the major practical algorithms for structured sparse recovery of speech signal. Speci ...

2012

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.