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4d Lorentzian Holst action with topological termsFeb 19 2009We study the Hamiltonian formulation of the general first order action of general relativity compatible with local Lorentz invariance and background independence. The most general simplectic structure (compatible with diffeomorphism invariance and local ... More

Taming VAEsOct 01 2018In spite of remarkable progress in deep latent variable generative modeling, training still remains a challenge due to a combination of optimization and generalization issues. In practice, a combination of heuristic algorithms (such as hand-crafted annealing ... More

Variational Inference with Normalizing FlowsMay 21 2015Jun 14 2016The choice of approximate posterior distribution is one of the core problems in variational inference. Most applications of variational inference employ simple families of posterior approximations in order to allow for efficient inference, focusing on ... More

Variational Information Maximisation for Intrinsically Motivated Reinforcement LearningSep 29 2015The mutual information is a core statistical quantity that has applications in all areas of machine learning, whether this is in training of density models over multiple data modalities, in maximising the efficiency of noisy transmission channels, or ... More

Variational inference for Monte Carlo objectivesFeb 22 2016Jun 01 2016Recent progress in deep latent variable models has largely been driven by the development of flexible and scalable variational inference methods. Variational training of this type involves maximizing a lower bound on the log-likelihood, using samples ... More

The theta parameter in loop quantum gravity: effects on quantum geometry and black hole entropyNov 20 2007The precise analog of the theta-quantization ambiguity of Yang-Mills theory exists for the real SU(2) connection formulation of general relativity. As in the former case theta labels representations of large gauge transformations, which are super-selection ... More

Variational Intrinsic ControlNov 22 2016In this paper we introduce a new unsupervised reinforcement learning method for discovering the set of intrinsic options available to an agent. This set is learned by maximizing the number of different states an agent can reliably reach, as measured by ... More

Normalizing Flows on Riemannian ManifoldsNov 07 2016Nov 09 2016We consider the problem of density estimation on Riemannian manifolds. Density estimation on manifolds has many applications in fluid-mechanics, optics and plasma physics and it appears often when dealing with angular variables (such as used in protein ... More

Beyond Greedy Ranking: Slate Optimization via List-CVAEMar 05 2018May 24 2018The conventional approach to solving the recommendation problem is through greedy ranking by prediction scores for individual document candidates. However these methods fail to optimize the slate as a whole, and often struggle at capturing biases caused ... More

Interaction Networks for Learning about Objects, Relations and PhysicsDec 01 2016Reasoning about objects, relations, and physics is central to human intelligence, and a key goal of artificial intelligence. Here we introduce the interaction network, a model which can reason about how objects in complex systems interact, supporting ... More

Towards Principled Unsupervised LearningNov 19 2015Dec 03 2015General unsupervised learning is a long-standing conceptual problem in machine learning. Supervised learning is successful because it can be solved by the minimization of the training error cost function. Unsupervised learning is not as successful, because ... More

DRAW: A Recurrent Neural Network For Image GenerationFeb 16 2015May 20 2015This paper introduces the Deep Recurrent Attentive Writer (DRAW) neural network architecture for image generation. DRAW networks combine a novel spatial attention mechanism that mimics the foveation of the human eye, with a sequential variational auto-encoding ... More

Generative Temporal Models with Spatial Memory for Partially Observed EnvironmentsApr 25 2018Jul 19 2018In model-based reinforcement learning, generative and temporal models of environments can be leveraged to boost agent performance, either by tuning the agent's representations during training or via use as part of an explicit planning mechanism. However, ... More

Towards Conceptual CompressionApr 29 2016We introduce a simple recurrent variational auto-encoder architecture that significantly improves image modeling. The system represents the state-of-the-art in latent variable models for both the ImageNet and Omniglot datasets. We show that it naturally ... More

Unsupervised Learning of 3D Structure from ImagesJul 03 2016Jun 19 2018A key goal of computer vision is to recover the underlying 3D structure from 2D observations of the world. In this paper we learn strong deep generative models of 3D structures, and recover these structures from 3D and 2D images via probabilistic inference. ... More

Consistent Jumpy Predictions for Videos and ScenesJul 05 2018Oct 02 2018Stochastic video prediction models take in a sequence of image frames, and generate a sequence of consecutive future image frames. These models typically generate future frames in an autoregressive fashion, which is slow and requires the input and output ... More

The Sturm-Liouville problem and the Polar Representation TheoremJun 29 2010The polar representation theorem for the n-dimensional time-dependent linear Hamiltonian system with continuous coefficients, states that, given two isotropic solutions (Q1, P1) and (Q2, P2), with the identity matrix as Wronskian,the formula Q2 = rcos(f), ... More

Conditional Neural ProcessesJul 04 2018Deep neural networks excel at function approximation, yet they are typically trained from scratch for each new function. On the other hand, Bayesian methods, such as Gaussian Processes (GPs), exploit prior knowledge to quickly infer the shape of a new ... More

Learning and Querying Fast Generative Models for Reinforcement LearningFeb 08 2018A key challenge in model-based reinforcement learning (RL) is to synthesize computationally efficient and accurate environment models. We show that carefully designed generative models that learn and operate on compact state representations, so-called ... More

Stochastic Backpropagation and Approximate Inference in Deep Generative ModelsJan 16 2014May 30 2014We marry ideas from deep neural networks and approximate Bayesian inference to derive a generalised class of deep, directed generative models, endowed with a new algorithm for scalable inference and learning. Our algorithm introduces a recognition model ... More

Periodical plane puzzles with numbersJun 06 2011Consider a periodical (in two independent directions) tiling of the plane with polygons (faces). In this article we shall only give examples using squares, regular hexagons, equilateral triangles and parallelograms ("unions" of two equilateral triangles). ... More

A contribution for a mathematical classification of square tilesJun 16 2012In this article we study some geometric properties of a non-trivial square tile (a non-trivial square tile is a non-constant function on a square). Consider infinitely many copies of this single square tile and cover the plane with them, without gaps ... More

Semi-Supervised Learning with Deep Generative ModelsJun 20 2014Oct 31 2014The ever-increasing size of modern data sets combined with the difficulty of obtaining label information has made semi-supervised learning one of the problems of significant practical importance in modern data analysis. We revisit the approach to semi-supervised ... More

Variational Memory Addressing in Generative ModelsSep 21 2017Aiming to augment generative models with external memory, we interpret the output of a memory module with stochastic addressing as a conditional mixture distribution, where a read operation corresponds to sampling a discrete memory address and retrieving ... More

Towards a Definition of Disentangled RepresentationsDec 05 2018How can intelligent agents solve a diverse set of tasks in a data-efficient manner? The disentangled representation learning approach posits that such an agent would benefit from separating out (disentangling) the underlying structure of the world into ... More

Learning models for visual 3D localization with implicit mappingJul 04 2018Dec 12 2018We consider learning based methods for visual localization that do not require the construction of explicit maps in the form of point clouds or voxels. The goal is to learn an implicit representation of the environment at a higher, more abstract level. ... More

The Riemann Magneton of the PrimesApr 12 2004Dec 07 2005We present a calculation involving a function related to the Riemann Zeta function and suggested by two recent works concerning the Riemann Hypothesis: one by Balazard, Saias and Yor and the other by Volchkov. We define an integral m (r) involving the ... More

Energy transport and fluctuations in small conductorsOct 22 2010Dec 22 2010The Landauer-B\"uttiker formalism provides a simple and insightful way for investigating many phenomena in mesoscopic physics. By this approach we derive general formulas for the energy properties and apply them to the basic setups. Of particular interest ... More

Markov subshifts and partial representation of F_nJul 03 2001In this paper we fix a set \Lambda^* of positive elements of the free group F_n (e.g. the set of finite words occurring in a Markov subshift) as well as n partial isometries on a Hilbert space H. Based on these we define a map S:F_n --> L(H) which we ... More

Unsupervised Learning of 3D Structure from ImagesJul 03 2016A key goal of computer vision is to recover the underlying 3D structure from 2D observations of the world. In this paper we learn strong deep generative models of 3D structures, and recover these structures from 3D and 2D images via probabilistic inference. ... More

Unsupervised Predictive Memory in a Goal-Directed AgentMar 28 2018Animals execute goal-directed behaviours despite the limited range and scope of their sensors. To cope, they explore environments and store memories maintaining estimates of important information that is not presently available. Recently, progress has ... More

One-Shot Generalization in Deep Generative ModelsMar 16 2016May 25 2016Humans have an impressive ability to reason about new concepts and experiences from just a single example. In particular, humans have an ability for one-shot generalization: an ability to encounter a new concept, understand its structure, and then be ... More

On ELSV-type formulae, Hurwitz numbers and topological recursionMar 19 2017We present several recent developments on ELSV-type formulae and topological recursion concerning Chiodo classes and several kind of Hurwitz numbers. The main results appeared in D. Lewanski, A. Popolitov, S. Shadrin, D. Zvonkine, "Chiodo formulas for ... More

Introduction to Perl module lb2d.pm 0.1 for basic Lattice Boltzmann simulationsFeb 02 2012Feb 03 2014The Lattice Boltzmann method has been gaining acceptance for hydrodynamic problems involving complex boundaries, non-equilibrium dynamics and interfacial phenomena in multiphase or multicomponent systems. lb2d.pm is a Perl module offering a clear framework ... More

Can We Prove Goldbach's Conjecture?Jul 21 2010Dec 26 2010In this paper we will propose a strategy to prove Goldbach's conjecture: every even integer greater than 2 can be written as the sum of two primes.

Generative Temporal Models with MemoryFeb 15 2017Feb 21 2017We consider the general problem of modeling temporal data with long-range dependencies, wherein new observations are fully or partially predictable based on temporally-distant, past observations. A sufficiently powerful temporal model should separate ... More

Neural ProcessesJul 04 2018A neural network (NN) is a parameterised function that can be tuned via gradient descent to approximate a labelled collection of data with high precision. A Gaussian process (GP), on the other hand, is a probabilistic model that defines a distribution ... More

Discrete Conley Index for Zero-dimensional Basic SetsApr 15 2015A theorem is established where the computation of the discrete Conley index for zero dimensional basic sets is given with respect to the dynamical information contained in the associated structure matrices. A classification of the reduced homology Conley ... More

Global phase portrait of a SIS modelMay 28 2012Jun 05 2012In the qualitative theory of ordinary differential equations, we can find many papers whose objective is the classification of all the possible topological phase portraits of a given family of differential system. Most of the studies rely on systems with ... More

On finite groups in which commutators are covered by Engel subgroupsJan 03 2019Let $m,n$ be positive integers and $w$ a multilinear commutator word. Assume that $G$ is a finite group having subgroups $G_1,\ldots,G_m$ whose union contains all $w$-values in $G$. Assume further that all elements of the subgroups $G_1,\ldots,G_m$ are ... More

An Explicit Construction of Systematic MDS Codes with Small Sub-packetization for All-Node RepairJun 08 2018Jun 25 2018An explicit construction of systematic MDS codes, called HashTag+ codes, with arbitrary sub-packetization level for all-node repair is proposed. It is shown that even for small sub-packetization levels, HashTag+ codes achieve the optimal MSR point for ... More

Infinite alphabet edge shift spaces via ultragraphs and their C*-algebrasMar 15 2017May 18 2017We define a notion of (one-sided) edge shift spaces associated to ultragraphs. In the finite case our notion coincides with the edge shift space of a graph. In general, we show that our space is metrizable and has a countable basis of clopen sets. We ... More

Branching systems and representations of Cohn-Leavitt path algebras of separated graphsMar 06 2014We construct for each separated graph (E;C) a family of branching systems over a set X and show how each branching system induces a representation of the Cohn-Leavitt path algebra associated to (E;C) as homomorphisms over the module of functions in X. ... More

The evolution of the rest-frame J- and H-band luminosity function of galaxies to z=3.5Nov 30 2011Nov 12 2012We present the rest-frame J- and H-band luminosity function (LF) of field galaxies, based on a deep multi-wavelength composite sample from the MUSYC, FIRES and FIREWORKS survey public catalogues, covering a total area of 450 arcmin^2. The availability ... More

Minimal model of financial stylized factsNov 27 2010Mar 09 2011In this work we afford the statistical characterization of a linear Stochastic Volatility Model featuring Inverse Gamma stationary distribution for the instantaneous volatility. We detail the derivation of the moments of the return distribution, revealing ... More

Unitary equivalence of representations of graph algebras and branching systemsNov 24 2009In this paper we show that, for a class of countable graphs, every representation of the associated graph algebra in a separable Hilbert space is unitarily equivalent to a representation obtained via branching systems.

Ultragraphs and shifts spaces over infinite alphabetsOct 15 2015Oct 16 2015In this paper we further develop the theory of one sided shift spaces over infinite alphabets, characterizing one-step shifts as edge shifts of ultragraphs and partially answering a conjecture regarding shifts of finite type (we show that there exists ... More

Riemann Hypothesis: a special case of the Riesz and Hardy-Littlewood wave and a numerical treatment of the Baez-Duarte coefficients up to some billions in the k-variableSep 17 2006We consider the Riesz and Hardy-Littlewood wave i.e. a ``critical function'' whose behaviour is concerned with the possible truth of the Riemann Hypothesis (RH). The function is studied numerically for the case alpha = 15/2 and beta = 4 in some range ... More

Stray capacitances in the watt balance operation: electrostatic forcesFeb 01 2014In a watt balance, stray capacitances exist between the coil and the magnet. Since the electric current flowing in the coil originates a difference between the coil and magnet electric-potentials, their electrostatic interactions must be taken into account. ... More

Perron-Frobenius operators and representations of the Cuntz-Krieger algebras for infinite matricesAug 06 2008In this paper we extend work of Kawamura, see kawamura, for Cuntz-Krieger algebras O_A for infinite matrices A. We generalize the definition of branching systems, prove their existence for any given matrix A and show how they induce some very concrete ... More

The criteria of Riesz, Hardy-Littlewood et al. for the Riemann Hypothesis revisited using similar functionsJan 07 2006The original criteria of Riesz and of Hardy-Littlewood concerning the truth of the Riemann Hypothesis (RH) are revisited and further investigated in light of the recent formulations and results of Maslanka and of Baez-Duarte concerning a representation ... More

Sensitivity of wide band detectors to quintessential gravitonsMay 20 1999There are no reasons why the energy spectra of the relic gravitons, amplified by the pumping action of the background geometry, should not increase at high frequencies. A typical example of this behavior are quintessential inflationary models where the ... More

Statistical inference for time-inhomogeneous volatility modelsJun 22 2004This paper offers a new approach for estimating and forecasting the volatility of financial time series. No assumption is made about the parametric form of the processes. On the contrary, we only suppose that the volatility can be approximated by a constant ... More

Bounded Engel elements in residually finite groupsDec 11 2018Let $q$ be a prime. Let $G$ be a residually finite group satisfying an identity. Suppose that for every $x \in G$ there exists a $q$-power $m=m(x)$ such that the element $x^m$ is a bounded Engel element. We prove that $G$ is locally virtually nilpotent. ... More

Dynamics for a class of polynomial maps in $\mathbb{R}^2$Dec 30 2017In this work we consider a class of endomorphisms of $\mathbb{R}^2$ defined by $f(x,y)=(xy+c,x)$, where $c\in\mathbb{R}$ is a real number and we prove that when $-1<c<0$, the forward (respectively backward) filled Julia set of $f$ is the union of stable ... More

Projected Quasi-particle Perturbation theoryMay 24 2012The BCS and/or HFB theories are extended by treating the effect of four quasi-particle states perturbatively. The approach is tested on the pairing hamiltonian, showing that it combines the advantage of standard perturbation theory valid at low pairing ... More

Leavitt path algebras as partial skew group ringsFeb 13 2012We realize Leavitt path algebras as partial skew group rings and give new proofs, based on partial skew group ring theory, of the Cuntz-Krieger uniqueness theorem and simplicity criteria for Leavitt path algebras.

Violation of the Energy Conservation Law in Lorentz-Dirac Equations for More Than One ChargeDec 30 1994An exact solution of Lorentz-Dirac equations where the energy conservation law is violated, is described herein for the case of two charges.

Interference Rate of Radiation of 2 Charges in Circular MotionDec 30 1994We present an exact formula for the computation of the interference rate of radiation in the case of two charges revolving with constant angular velocity at opposite ends of a diameter in a fixed circle. The formula is valid for arbitrary velocities of ... More

Simplicity and chain conditions for ultragraph Leavitt path algebras via partial skew group ring theoryJun 12 2017Jun 13 2017We realize Leavitt ultragraph path algebras as partial skew group rings. Using this realization we characterize artinian ultragraph path algebras and give simplicity criteria for these algebras.

Families of Optimal Binary Non-MDS Erasure CodesSep 08 2016We introduce a definition for \emph{Families of Optimal Binary Non-MDS Erasure Codes} for $[n, k]$ codes over $GF(2)$, and propose an algorithm for finding those families by using hill climbing techniques over Balanced XOR codes. Due to the hill climbing ... More

On the mKdV-Liouville hierarchy and its self-similarity reductionJun 22 2014Integrable mixed models have been used as a generalization of traditional integrable models. However, a map from a traditional integrable model to a mixed integrable model is not well understood yet. Here, it is studied the relation between the mKdV-Liouville ... More

(M + 1)-step shift spaces that are not conjugate to M-step shift spacesMay 28 2014Jun 27 2014Recently Ott, Tomforde and Willis proposed a new approach for one sided shift spaces over infinite alphabets. In this new approach the conjugacy classes of shifts of finite type, edge shifts, and M-step shifts are distinct and the authors conjecture that ... More

Online Multilinear Dictionary Learning for Sequential Compressive SensingMar 07 2017Mar 16 2017A method for online tensor dictionary learning is proposed. With the assumption of separable dictionaries, tensor contraction is used to diminish a $N$-way model of $\mathcal{O}\left(L^N\right)$ into a simple matrix equation of $\mathcal{O}\left(NL^2\right)$ ... More

C*-algebras Associated do Stationary Ordered Bratteli DiagramsAug 18 2011Aug 23 2011In this paper, we introduce a C*-algebra associated to any substitution (via its Bratteli diagram model). We show that this C*-algebra contains the partial crossed product C*-algebra of the corresponding Bratteli-Vershik system and show that these algebras ... More

$\mathcal{W}$-algebra constraints and topological recursion for $A_N$-singularityFeb 29 2016We derive a Bouchard--Eynard type topological recursion for the total descendant potential of $A_N$-singularity. Our argument relies on a certain twisted representation of a Heisenberg Vertex Operator Algebra (VOA) constructed via the periods of $A_N$-singularity. ... More

Response of VIRGO detectors to pre-big-bang gravitonsAug 04 2001The sensitivity achievable by a pair of VIRGO detectors to stochastic and isotropic gravitational wave backgrounds produced in pre-big-bang models is discussed in view of the development of a second VIRGO interferometer. We describe a semi-analytical ... More

Few-shot Autoregressive Density Estimation: Towards Learning to Learn DistributionsOct 27 2017Feb 28 2018Deep autoregressive models have shown state-of-the-art performance in density estimation for natural images on large-scale datasets such as ImageNet. However, such models require many thousands of gradient-based weight updates and unique image examples ... More

Joining relations under discrete uncertaintyNov 01 2012In this paper we introduce and experimentally compare alternative algorithms to join uncertain relations. Different algorithms are based on specific principles, e.g., sorting, indexing, or building intermediate relational tables to apply traditional approaches. ... More

A class of adding machine and Julia setsAug 20 2015In this work we define a stochastic adding machine associated to the Fibonacci base and to a probabilities sequence $\overline{p}=(p_i)_{i\geq 1}$. We obtain a Markov chain whose states are the set of nonnegative integers. We study probabilistic properties ... More

Quantum Integrals from Coalgebra StructureOct 16 2014Quantum versions of the hydrogen atom and the harmonic oscillator are studied on non Euclidean spaces of dimension N. 2N-1 integrals, of arbitrary order, are constructed via a multi-dimensional version of the factorization method, thus confirming the ... More

Sensitivity of a VIRGO pair to stochastic GW backgroundsAug 16 2000The sensitivity of a pair of VIRGO interferometers to gravitational waves backgrounds (GW) of cosmological origin is analyzed for the cases of maximal and minimal overlap of the two detectors. The improvements in the detectability prospects of scale-invariant ... More

Packing coloring of generalized Sierpinski graphsSep 26 2018Feb 07 2019The packing chromatic number $\chi_{\rho}(G)$ of a graph $G$ is the smallest integer $c$ such that the vertex set $V(G)$ can be partitioned into sets $X_1, . . . , X_c$, with the condition that vertices in $X_i$ have pairwise distance greater than $i$. ... More

Rate of approximation for multivariate sampling Kantorovich operators on some functions spacesNov 09 2014In this paper, the problem of the order of approximation for the multivariate sampling Kantorovich operators is studied. The cases of the uniform approximation for uniformly continuous and bounded functions/signals belonging to Lipschitz classes and the ... More

A Probabilistic U-Net for Segmentation of Ambiguous ImagesJun 13 2018Jan 29 2019Many real-world vision problems suffer from inherent ambiguities. In clinical applications for example, it might not be clear from a CT scan alone which particular region is cancer tissue. Therefore a group of graders typically produces a set of diverse ... More

Representations and the reduction theorem for ultragraph Leavitt path algebrasJan 31 2019In this paper we study representations of ultragraph Leavitt path algebras via branching systems and, using partial skew ring theory, prove the reduction theorem for these algebras. We apply the reduction theorem to show that ultragraph Leavitt path algebras ... More

Dependence of microwave absorption properties on ferrite volume fraction in MnZn ferrite/rubber radar absorbing materialsMay 30 2011We report the analysis of measurements of the complex magnetic permeability ($\mu_r$) and dielectric permittivity ($\epsilon_r$) spectra of a rubber radar absorbing material (RAM) with various MnZn ferrite volume fractions. The transmission/reflection ... More

A Self-Consistent Extrapolation Method for the Complex Permittivity and Permeability Based on Finite Frequency DataFeb 14 2014Dec 04 2014We describe a method of extrapolation based on a "truncated" Kramers-Kronig relation for the complex permittivity ($\epsilon$) and permeability ($\mu$) parameters of a material, based on finite frequency data. Considering a few assumptions, such as the ... More

An experimental comparison of label selection methods for hierarchical document clustersMay 24 2018The focus of this paper is on the evaluation of sixteen labeling methods for hierarchical document clusters over five datasets. All of the methods are independent from clustering algorithms, applied subsequently to the dendrogram construction and based ... More

The geometry of quadratic polynomial differential systems with a finite and an infinite saddle-node (A,B)Mar 06 2013The goal is to make a global study of the family QsnSN of all real quadratic polynomial differential systems which have a finite semi-elemental saddle-node and an infinite saddle-node formed by the collision of two infinite singular points. This family ... More

Global phase portraits of quadratic polynomial differential systems with a semi-elemental triple nodeDec 29 2012Planar quadratic differential systems occur in many areas of applied mathematics. Although more than one thousand papers have been written on these systems, a complete understanding of this family is still missing. Classical problems, and in particular, ... More

The Theory of Quaternion Matrix DerivativesOct 01 2014A systematic theory is introduced for calculating the derivatives of quaternion matrix function with respect to quaternion matrix variables. The proposed methodology is equipped with the matrix product rule and chain rule and it is able to handle both ... More

Polyelectrolyte intelligent gels. Design and applicationsJun 21 2012In this chapter polyelectrolyte intelligent gels are examined along three broad lines. The effects of different physical, chemical and biological stimuli on gels response are analysed and mechanisms of response are outlined. The broad range of biomedical ... More

Security for Wiretap Networks via Rank-Metric CodesDec 29 2007May 02 2008The problem of securing a network coding communication system against a wiretapper adversary is considered. The network implements linear network coding to deliver $n$ packets from source to each receiver, and the wiretapper can eavesdrop on $\mu$ arbitrarily ... More

Fast Encoding and Decoding of Gabidulin CodesJan 16 2009Apr 05 2009Gabidulin codes are the rank-metric analogs of Reed-Solomon codes and have a major role in practical error control for network coding. This paper presents new encoding and decoding algorithms for Gabidulin codes based on low-complexity normal bases. In ... More

On the joint distribution of first-passage time and first-passage area of drifted Brownian motionSep 22 2016For drifted Brownian motion $X(t)= x - \mu t + B_t \ (\mu >0)$ starting from $x>0,$ we study the joint distribution of the first-passage time below zero, $\tau(x),$ and the first-passage area, $A(x),$ swept out by $X$ till the time $\tau(x).$ In particular, ... More

Determinant and Weyl anomaly of Dirac operator: a holographic derivationNov 07 2011Nov 18 2011We present a holographic formula relating functional determinants: the fermion determinant in the one-loop effective action of bulk spinors in an asymptotically locally AdS background, and the determinant of the two-point function of the dual operator ... More

AdS Chern-Simons Gravity induces Conformal GravityNov 21 2013Dec 25 2013The leitmotif of this paper is the question of whether four- and higher even-dimensional Conformal Gravities do have a Chern-Simons pedigree. We show that Weyl gravity can be obtained as dimensional reduction of a five-dimensional Chern-Simons action ... More

Assessing the Predictive Power of Galaxy Formation Models with the Rest-Frame Optical Luminosity Functions at 2.0<z<3.3Jan 10 2008We compare recently measured rest-frame V-band luminosity functions (LFs) of galaxies at redshifts 2.0<z<3.3 to predictions of semianalytic models by De Lucia & Blaizot and Bower et al. and hydrodynamic simulations by Dave et al. The models succeed for ... More

Assessing the Predictive Power of Galaxy Formation Models: A Comparison of Predicted and Observed Rest-Frame Optical Luminosity Functions at 2.0<z<3.3May 29 2007Jan 07 2008Recent galaxy formation models successfully reproduce the local luminosity function (LF) of galaxies by invoking mechanisms to suppress star formation in low- and high-mass galaxies. As these models are optimized to fit the LF at low redshift, a crucial ... More

Partition functions and double-trace deformations in AdS/CFTFeb 20 2007Feb 19 2008We study the effect of a relevant double-trace deformation on the partition function (and conformal anomaly) of a CFT at large N and its dual picture in AdS. Three complementary previous results are brought into full agreement with each other: bulk and ... More

On the AdS Higher Spin / O(N) Vector Model Correspondence: degeneracy of the holographic imageMar 10 2006May 04 2006We explore the conjectured duality between the critical O(N) vector model and minimal bosonic massless higher spin (HS) theory in AdS. In the boundary free theory, the conformal partial wave expansion (CPWE) of the four-point function of the scalar singlet ... More

Scattering coefficients and bound states for high-energy transparent $δ-δ^{\prime}$ interactionsJul 21 2016We propose a model for energy-dependent $\delta-\delta^{\prime}$ interactions which yields scattering coefficients exhibiting full transmission for high-energy incident particles, also computing the bound solutions in one-dimension nonrelativistic quantum ... More

Casimir force between $δ-δ^{\prime}$ mirrors transparent at high frequenciesJul 21 2016Nov 01 2016We investigate, in the context of a real massless scalar field in $1+1$ dimensions, models of partially reflecting mirrors simulated by Dirac $\delta-\delta^{\prime}$ point interactions. In the literature, these models do not exhibit full transparency ... More

Machine learning for precision psychiatryMay 30 2017The nature of mental illness remains a conundrum. Traditional disease categories are increasingly suspected to mis-represent the causes underlying mental disturbance. Yet, psychiatrists and investigators now have an unprecedented opportunity to benefit ... More

Generating Predicate Callback Summaries for the Android FrameworkMar 27 2017Mar 29 2017One of the challenges of analyzing, testing and debugging Android apps is that the potential execution orders of callbacks are missing from the apps' source code. However, bugs, vulnerabilities and refactoring transformations have been found to be related ... More

Flexible behavioral capture-recapture modellingJan 24 2014We develop some new strategies for building and fitting new flexible classes of parametric capture-recapture models for closed populations which can be used to address a better understanding of behavioural patterns. We first rely on a conditional probability ... More

A Unifying Approach to Quaternion Adaptive Filtering: Addressing the Gradient and ConvergenceOct 17 2013A novel framework for a unifying treatment of quaternion valued adaptive filtering algorithms is introduced. This is achieved based on a rigorous account of quaternion differentiability, the proposed I-gradient, and the use of augmented quaternion statistics ... More

Designing a robustly metallic noncenstrosymmetric ruthenate oxide with large thermopower anisotropyOct 04 2013Mar 18 2014The existence of approximately 30 noncentrosymmetric metals (NCSM) suggests a contraindication between crystal structures without inversion symmetry and metallic behavior. Those containing oxygen are especially scarce. Here we propose and demonstrate ... More

Universal Secure Network Coding via Rank-Metric CodesSep 21 2008Apr 27 2010The problem of securing a network coding communication system against an eavesdropper adversary is considered. The network implements linear network coding to deliver n packets from source to each receiver, and the adversary can eavesdrop on \mu arbitrarily ... More