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Related papers: A replica approach to the state-dependent synapses…

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We present a simple model that recalls two different patterns depending on the temperature. To realize a change in recall pattern due to temperature change, we embed two patterns to different graphs: the first pattern into a fully connected…

Disordered Systems and Neural Networks · Physics 2026-02-25 Munetaka Sasaki

Recently authors have introduced the idea of training discrete weights neural networks using a mix between classical simulated annealing and a replica ansatz known from the statistical physics literature. Among other points, they claim…

Machine Learning · Computer Science 2021-03-17 Vincent Gripon , Matthias Löwe , Franck Vermet

State-machine replication, a fundamental approach to fault tolerance, requires replicas to execute commands deterministically, which usually results in sequential execution of commands. Sequential execution limits performance and underuses…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-04-29 Parisa Jalili Marandi , Fernando Pedone

In an era where we can not afford to checkpoint frequently, replication is a generic way forward to construct numerical simulations that can continue to run even if hardware parts fail. Yet, replication often is not employed on larger…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-02 Philipp Samfass , Tobias Weinzierl , Benjamin Hazelwood , Michael Bader

We present results for two different kinds of high order connections between neurons acting as corrections to the Hopfield model. Equilibrium properties are analyzed using the replica mean-field theory and compared with numerical…

Condensed Matter · Physics 2009-10-22 J. J. Arenzon , R. M. C. de Almeida

Reinforcement learning has long struggled with poor sample efficiency. One promising approach to mitigate this problem is leveraging group-invariant Markov Decision Processes ($G$-invariant MDPs). Existing works in this direction have…

Machine Learning · Computer Science 2026-05-25 Shuai Zhen , Yifan Zhang , Yuling Wang , Yanhua Yu

We study systems without quenched disorder with a complex landscape, and we use replica symmetry theory to describe them. We discuss the Golay-Bernasconi-Derrida approximation of the low autocorrelation model, and we reconstruct it by using…

High Energy Physics - Theory · Physics 2009-10-28 E. Marinari , G. Parisi , F. Ritort

The critical behaviour of the dynamical transition of glassy system is controlled by a Replica Symmetric action with n=1 replicas. The most divergent diagrams in the loop expansion correspond at all orders to the solutions of a stochastic…

Statistical Mechanics · Physics 2011-05-27 Silvio Franz , Giorgio Parisi , Federico Ricci-Tersenghi , Tommaso Rizzo

A single McCulloch-Pitts neuron, that is, the simple perceptron is studied, with focus on the region beyond storage capacity. It is shown that Parisi's hierarchical ansatz for the overlap matrix of the synaptic couplings with so called…

Disordered Systems and Neural Networks · Physics 2015-06-24 G. Gyorgyi , P. Reimann

We use the replica method in order to obtain an expression for the variational free energy of an Ising ferromagnet on a Viana-Bray lattice in the presence of random external fields. Introducing a global order parameter, in the…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. O. Hase , J. R. L. de Almeida , S. R. Salinas

We study the partition-function zeros in mean-field spin-glass models. We show that the replica method is useful to find the locations of zeros in a complex parameter plane. For the random energy model, we obtain the phase diagram in the…

Disordered Systems and Neural Networks · Physics 2015-03-17 Kazutaka Takahashi

Infinite-range spin-glass models with Levy-distributed interactions show a freezing transition similar to disordered spin systems on finite connectivity random graphs. It is shown that despite diverging moments of the local field…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Engel

Replay in neural networks involves training on sequential data with memorized samples, which counteracts forgetting of previous behavior caused by non-stationarity. We present a method where these auxiliary samples are generated on the fly,…

Machine Learning · Computer Science 2020-12-15 Xu Ji , Joao Henriques , Tinne Tuytelaars , Andrea Vedaldi

We recently introduced a novel replica-exchange scheme in which an individual replica can sample from states encountered by other replicas at any previous time by way of a global configuration database, enabling the fast propagation of…

Computational Physics · Physics 2015-12-15 Thomas Vogel , Danny Perez

p-Adic and noncommutative analysis are applied to describe phase transitions in disordered systems. In the noncommutative replica approach we replicate the disorder instead of the system degrees of freedom. The noncommutatibe replica…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. V. Kozyrev

We extend Neural Processes (NPs) to sequential data through Recurrent NPs or RNPs, a family of conditional state space models. RNPs model the state space with Neural Processes. Given time series observed on fast real-world time scales but…

Machine Learning · Computer Science 2019-11-07 Timon Willi , Jonathan Masci , Jürgen Schmidhuber , Christian Osendorfer

In this talk we review our theoretical understanding of spin glasses paying a particular attention to the basic physical ideas. We introduce the replica method and we describe its probabilistic consequences (we stress the recently…

Disordered Systems and Neural Networks · Physics 2007-05-23 Giorgio Parisi

In this thesis, we review and examine the replica method from several viewpoints. The replica method is a mathematical technique to calculate general moments of stochastic variables. This method provides a systematic way to evaluate…

Statistical Mechanics · Physics 2015-08-24 Tomoyuki Obuchi

In a previous report we have evaluated analytically the mutual information between the firing rates of N independent units and a set of multi-dimensional continuous+discrete stimuli, for a finite population size and in the limit of large…

Disordered Systems and Neural Networks · Physics 2007-05-23 Valeria Del Prete , Alessandro Treves

Equilibrium states of large layered neural networks with differentiable activation function and a single, linear output unit are investigated using the replica formalism. The quenched free energy of a student network with a very large…

Disordered Systems and Neural Networks · Physics 2009-10-31 Martin Ahr , Michael Biehl , Robert Urbanczik