Convergence condition of the TAP equation for the infinite-ranged Ising spin glass model
By T. Plefka. 1982
Subfields: AI for Physical Sciences
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In AI for Physical Sciences
- Florent Krzakala
- Christopher Sander
- Manfred Opper
- Hedvig Kjellström
- Ole Winther
- Ned S. Wingreen
- Anne-Florence Bitbol
- Cheng Zhang
Citations in the corpus
- Revealing evolutionary constraints on proteins through sequence analysis (2018, background): “The expansion can be extended to higher order, and the second-order expansion is known as the Thouless, Anderson, and Palmer (TAP) free energy [50,59].”
- Direct-coupling analysis of residue coevolution captures native contacts across many protein families (2011, background): “he iterative message-passing solver results from the fact that parameter inference can be done in a single computational step in the new algorithm. The approach is based on a small-coupling expansion (47, 48), which is explained in detail in the Supplement: The exponential of € Σ i<j e ij (A i ,A”
- Protein structure prediction from sequence variation (2012, methodology): “This was superseded by a much more efficient mean-field approximation, in which the parameter estimation problem was solved statistical inference 37–39 , and the conditional mutual information derived from correlations between positions in a protein sequence is a discrete, nonlinear analog of…”
- Electronic structure calculations with dynamical mean-field theory (2005, methodology): “The strategy consists in performing an expansion of the functional in powers of electron charge Plefka, 1982; Fukuda, 1988; Georges and Yedidia, 1991a; Fukuda et al., 1994; Valiev and Fernando, 1997; Chitra and Kotliar, 2001; Georges, 2002 .”
- Advances in Variational Inference (2017, methodology): “This connects to earlier work on TAP equations [150], [190] (see Section 5.1), which generally did not result in a bound.”
- Statistical physics of inference: thresholds and algorithms (2015, background): “Interestingly, these equations can be seen as “improved” variational mean-field equations, and this is at the roots of many perturbation approaches (such as Plefka/Yedidia-Georges [107, 253] or Kikuchi [163]).”
- Expectation Consistent Approximate Inference (2005, background): “(63) For the second order term of this so-called Plefka expansion see, e.g. Plefka (1982) and several contributions in Opper and Saad (2001).”