Efficient Computation of Shap Explanation Scores for Neural Network Classifiers via Knowledge Compilation

The use of Shap scores has become widespread in Explainable AI. However, their computation is in general intractable, in particular when done with a black-box classifier, such as neural network. Recent research has unveiled classes of open-box Boolean Circuit classifiers for which Shap can be computed efficiently. We show how to transform binary neural networks into those circuits for efficient Shap computation. We use logic-based knowledge compilation techniques. The performance gain is huge, as we show in the light of our experiments.Comment: Conference submission. It replaces the previously uploaded paper "Opening Up the Neural Network Classifier for Shap Score Computation", by the same authors. This version considerably revised the previous on

Present and future self in memory: the role of vmPFC in the self-reference effect

Self-related information is remembered better than other-related information (self-reference effect; SRE), a phenomenon that has been convincingly linked to the medial prefrontal cortex. It is not clear whether information related to our future self would also have a privileged status in memory, as medial prefrontal cortex (mPFC) regions respond less to the future than to the present self, as if it were an 'other'. Here we ask whether the integrity of the ventral mPFC (vmPFC) is necessary for the emergence of the present and future SRE, if any. vmPFC patients and brain-damaged and healthy controls judged whether each of a series of trait adjectives was descriptive of their present self, future self, another person and that person in the future and later recognized studied traits among distractors. Information relevant to the present (vs future) was generally recognized better, across groups. However, whereas healthy and brain-damaged controls exhibited strong present and future SREs, these were absent in vmPFC patients, who concomitantly showed reduced certainty about their own present and anticipated traits compared to the control groups. These findings indicate that vmPFC is necessary to impart a special mnemonic status to self-related information, including our envisioned future self, possibly by instantiating the self-schema

Ground state properties of a Tonks-Girardeau Gas in a periodic potential

In this paper, we investigate the ground-state properties of a bosonic Tonks-Girardeau gas confined in a one-dimensional periodic potential. The single-particle reduced density matrix is computed numerically for systems up to $N=265$ bosons. Scaling analysis of the occupation number of the lowest orbital shows that there are no Bose-Einstein Condensation(BEC) for the periodically trapped TG gas in both commensurate and incommensurate cases. We find that, in the commensurate case, the scaling exponents of the occupation number of the lowest orbital, the amplitude of the lowest orbital and the zero-momentum peak height with the particle numbers are 0, -0.5 and 1, respectively, while in the incommensurate case, they are 0.5, -0.5 and 1.5, respectively. These exponents are related to each other in a universal relation.Comment: 9 pages, 10 figure

Extension of Some Edge Graph Problems: Standard and Parameterized Complexity

Le PDF est une version auteur non publiée.We consider extension variants of some edge optimization problems in graphs containing the classical Edge Cover, Matching, and Edge Dominating Set problems. Given a graph G=(V,E) and an edge set U⊆E, it is asked whether there exists an inclusion-wise minimal (resp., maximal) feasible solution E′ which satisfies a given property, for instance, being an edge dominating set (resp., a matching) and containing the forced edge set U (resp., avoiding any edges from the forbidden edge set E∖U). We present hardness results for these problems, for restricted instances such as bipartite or planar graphs. We counter-balance these negative results with parameterized complexity results. We also consider the price of extension, a natural optimization problem variant of extension problems, leading to some approximation results

The prolyl-isomerase PIN1 is essential for nuclear Lamin-B structure and function and protects heterochromatin under mechanical stress

Chromatin organization plays a crucial role in tissue homeostasis. Heterochromatin relaxation and consequent unscheduled mobilization of transposable elements (TEs) are emerging as key contributors of aging and aging-related pathologies, including Alzheimer's disease (AD) and cancer. However, the mechanisms governing heterochromatin maintenance or its relaxation in pathological conditions remain poorly understood. Here we show that PIN1, the only phosphorylation-specific cis/trans prolyl isomerase, whose loss is associated with premature aging and AD, is essential to preserve heterochromatin. We demonstrate that this PIN1 function is conserved from Drosophila to humans and prevents TE mobilization-dependent neurodegeneration and cognitive defects. Mechanistically, PIN1 maintains nuclear type-B Lamin structure and anchoring function for heterochromatin protein 1\u3b1 (HP1\u3b1). This mechanism prevents nuclear envelope alterations and heterochromatin relaxation under mechanical stress, which is a key contributor to aging-related pathologies