61 citations · 153 across the 18 of their papers we have counts for
23 papers
A Single-Parameter Factor-Graph Image Prior
Tianyang Wang, Ender Konukoglu, Hans-Andrea Loeliger
We propose a novel piecewise smooth image model with piecewise constant local parameters that are automatically adapted to each image. Technically, the model is formulated in terms…
Continuous-Time Neural Networks Can Stably Memorize Random Spike Trains
Hugo Aguettaz, Hans-Andrea Loeliger
The paper explores the capability of continuous-time recurrent neural networks to store and recall precisely timed scores of spike trains. We show (by numerical experiments) that t…
Model-Predictive Control with NUP Priors
Raphael Keusch, Hans-Andrea Loeliger
Normals with unknown variance (NUV) and, more generally, normals with unknown parameters (NUP) can represent many useful priors including L_p norms and other sparsifying priors, an…
Calibrating Control-Bounded ADCs
Hampus Malmberg, Till Mettler, Thomas Burger +2
The paper considers the calibration of control-bounded analog-to-digital converters. It is demonstrated that variations of the analog frontend can be addressed by calibrating the d…
Half-Space and Box Constraints as NUV Priors: First Results
Raphael Keusch, Hans-Andrea Loeliger
Normals with unknown variance (NUV) can represent many useful priors and blend well with Gaussian models and message passing algorithms. NUV representations of sparsifying priors h…
A Binarizing NUV Prior and its Use for M-Level Control and Digital-to-Analog Conversion
Raphael Keusch, Hans-Andrea Loeliger
Priors with a NUV representation (normal with unknown variance) have mostly been used for sparsity. In this paper, a novel NUV prior is proposed that effectively binarizes. While s…
Binary Control and Digital-to-Analog Conversion Using Composite NUV Priors and Iterative Gaussian Message Passing
Raphael Keusch, Hampus Malmberg, Hans-Andrea Loeliger
The paper proposes a new method to determine a binary control signal for an analog linear system such that the state, or some output, of the system follows a given target trajector…
Control-Bounded Analog-to-Digital Conversion: Transfer Function Analysis, Proof of Concept, and Digital Filter Implementation
Hans-Andrea Loeliger, Hampus Malmberg, Georg Wilckens
Control-bounded analog-to-digital conversion has many commonalities with delta-sigma conversion, but it can profitably use more general analog filters. The paper describes the oper…
Online Memorization of Random Firing Sequences by a Recurrent Neural Network
Patrick Murer, Hans-Andrea Loeliger
This paper studies the capability of a recurrent neural network model to memorize random dynamical firing patterns by a simple local learning rule. Two modes of learning/memorizati…
Quantum Measurement as Marginalization and Nested Quantum Systems
Hans-Andrea Loeliger, Pascal O. Vontobel
In prior work, we have shown how the basic concepts and terms of quantum mechanics relate to factorizations and marginals of complex-valued quantum mass functions, which are genera…
Simultaneous Partial Inverses and Decoding Interleaved Reed-Solomon Codes
Jiun-Hung Yu, Hans-Andrea Loeliger
The paper introduces the simultaneous partial-inverse problem (SPI) for polynomials and develops its application to decoding interleaved Reed--Solomon codes beyond half the minimum…
On Sparsity by NUV-EM, Gaussian Message Passing, and Kalman Smoothing
Hans-Andrea Loeliger, Lukas Bruderer, Hampus Malmberg +2
Normal priors with unknown variance (NUV) have long been known to promote sparsity and to blend well with parameter learning by expectation maximization (EM). In this paper, we adv…
Factor Graphs for Quantum Probabilities
Hans-Andrea Loeliger, Pascal O. Vontobel
A factor-graph representation of quantum-mechanical probabilities (involving any number of measurements) is proposed. Unlike standard statistical models, the proposed representatio…
Partition Function of the Ising Model via Factor Graph Duality
Mehdi Molkaraie, Hans-Andrea Loeliger
The partition function of a factor graph and the partition function of the dual factor graph are related to each other by the normal factor graph duality theorem. We apply this res…
LMMSE Estimation and Interpolation of Continuous-Time Signals from Discrete-Time Samples Using Factor Graphs
Lukas Bolliger, Hans-Andrea Loeliger, Christian Vogel
The factor graph approach to discrete-time linear Gaussian state space models is well developed. The paper extends this approach to continuous-time linear systems/filters that are…
Reverse Berlekamp-Massey Decoding
Jiun-Hung Yu, Hans-Andrea Loeliger
We propose a new algorithm for decoding Reed-Solomon codes (up to half the minimum distance) and for computing inverses in . The proposed algorithm is similar in spirit…
Extending Monte Carlo Methods to Factor Graphs with Negative and Complex Factors
Mehdi Molkaraie, Hans-Andrea Loeliger
The partition function of a factor graph can sometimes be accurately estimated by Monte Carlo methods. In this paper, such methods are extended to factor graphs with negative and c…
On Polynomial Remainder Codes
Jiun-Hung Yu, Hans-Andrea Loeliger
Polynomial remainder codes are a large class of codes derived from the Chinese remainder theorem that includes Reed-Solomon codes as a special case. In this paper, we revisit these…
A Factor-Graph Representation of Probabilities in Quantum Mechanics
Hans-Andrea Loeliger, Pascal O. Vontobel
A factor-graph representation of quantum-mechanical probabilities is proposed. Unlike standard statistical models, the proposed representation uses auxiliary variables (state varia…
Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
Mehdi Molkaraie, Hans-Andrea Loeliger
The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source/channel models. The focus of the paper is on binary-input channels w…
Expectation Maximization as Message Passing - Part I: Principles and Gaussian Messages
Justin Dauwels, Andrew Eckford, Sascha Korl +1
It is shown how expectation maximization (EM) may be viewed as a message passing algorithm in factor graphs. In particular, a general EM message computation rule is identified. As…
A general computation rule for lossy summaries/messages with examples from equalization
Junli Hu, Hans-Andrea Loeliger, Justin Dauwels +1
Elaborating on prior work by Minka, we formulate a general computation rule for lossy messages. An important special case (with many applications in communications) is the conversi…
Expectation maximization as message passing
J. Dauwels, S. Korl, H. -A. Loeliger
Based on prior work by Eckford, it is shown how expectation maximization (EM) may be viewed, and used, as a message passing algorithm in factor graphs.