2020

• An extension of the second order dynamical system that models Nesterov’s convex gradient method

  C. D. Alecsa, S. C. László, & T. Pința. (2020)

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• Automated detection of presymptomatic conditions in spinocerebellar ataxia type 2 using Monte Carlo dropout and deep neural network techniques with electrooculogram signals

  C. Stoean, R. Stoean, M. Atencia, M. Abdar, L. Velázquez-Pérez, A. Khosravi, .... (2020)

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• New optimization algorithms for neural network training using operator splitting techniques

  C. D. Alecsa, T. Pința, & I. Boros. (2020)

  Neural Networks, 126, 178-190.
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• Management of water bodies in show caves – A microbial approach

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• Tumor Detection in Brain MRIs by Computing Dissimilarities in the Latent Space of a Variational AutoEncoder

  A. I. Albu, A. Enescu, & L. Malagò. (2020)

  In Proceedings of the Northern Lights Deep Learning WorkshopTromsø, Norway: Septentrio Academic Publishing.
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• Evaluating the Robustness of Defense Mechanisms based on AutoEncoder Reconstructions against Carlini-Wagner Adversarial Attacks

  P. Hlihor, R. Volpi, & L. Malagò. (2020)

  In Proceedings of the Northern Lights Deep Learning WorkshopTromsø, Norway: Proceedings of the Northern Lights Deep Learning Workshop.
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• Training highly effective connectivities within neural networks with randomly initialized, fixed weights

  C. Ivan, & R. V. Florian. (2020)

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• The long time behavior and the rate of convergence of symplectic convex algorithms obtained via splitting discretizations of inertial damping systems

  C. D. Alecsa. (2020)

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2019

• The Growth and Decline of the Western Roman Empire

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• Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations

  C. Stoean, W. Paja, R. Stoean, & A. Săndiță. (2019)

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• Deep Knowledge Based Agent: Learning to do tasks by self-thinking about imaginary worlds

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• Analyzing the theoretical grounds of curiosity-driven, intrinsically-motivated learning

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• Convolutional Neural Networks on Randomized Data

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  In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (p. 1-8).
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• On modelling emergence of logical thinking

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  In Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI. AAAI Spring Symposium.
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• Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks

  H. J. Hortúa, R. Volpi, D. Marinelli, & L. Malagò. (2019)

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• Natural Alpha Embeddings

  R. Volpi, & L. Malagò. (2019)

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2018

• Wasserstein Riemannian geometry of Gaussian densities

  L. Malagò, L. Montrucchio, & G. Pistone. (2018)

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• A continuous-time MaxSAT solver with high analog performance

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• Approximating hidden chaotic attractors via parameter switching

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• The mouse cortical connectome, characterized by an ultra-dense cortical graph, maintains specificity by distinct connectivity profiles

  R. Gămănuţ, H. Kennedy, Z. Toroczkai, M. Ercsey-Ravasz, D. C. Van Essen, K. Knoblauch, & A. Burkhalter. (2018)

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• Generalization of the Filippov method for systems with large periodic input

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  Mathematics and Computers in Simulation, 146, 1-13.
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• Fractional-order PWC systems without zero Lyapunov exponents

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  Nonlinear Dynamics, 92(3), 1061–1078.
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• Lyapunov exponents of a hyperchaotic discontinuous 4D system of integer or fractional order

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• Modeling cognitive processes underlying computer programming

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• Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds

  S. Sârbu, R. Volpi, A. Pește, & L. Malagò. (2018)

  In ICML 2018 Workshop on Theoretical Foundations and Applications of Deep Generative Models.
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• Using sequence to sequence neural networks for solving similar mathematical problems

  A. Davody, & M. S. Baba. (2018)

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• Learning to generate HTML code from images with no supervisory data

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  In Neural Abstract Machines & Program Induction v2: A Federated Artificial Intelligence Meeting (FAIM) workshop (ICML, IJCAI/ECAI, AAMAS).
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• Hierarchical segmentation of graphical interfaces for Document Object Model reconstruction

  C. F. Perțicaș, M. S. Baba, H. Davoudi, & R. V. Florian. (2018)

  In Neural Abstract Machines & Program Induction v2: A Federated Artificial Intelligence Meeting (FAIM) workshop (ICML, IJCAI/ECAI, AAMAS).
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• Applications of the f-divergence to variational inference

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2017

• Software categorization using low-level distributional features

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• Impulsive stabilization of chaos in fractional-order systems

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• Unusual dynamics and hidden attractors of the Rabinovich–Fabrikant system

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  Nonlinear Dynamics, 88(1), 791–805.
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• A multiscale cerebral neurochemical connectome of the rat brain

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• Hidden chaotic attractors in fractional-order systems

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  Nonlinear Dynamics, 89(1), 577–586.
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• Impulsive stabilization of chaos in fractional-order systems

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• On the numerical integration of discontinuous dynamical systems

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  International Journal of Bifurcation and Chaos, 27(14), 1750218.
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• Parameter Switching Synchronization

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  Applied Mathematics and Computation, 313, 94-102.
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• An Explanatory Analysis of the Geometry of Latent Variables Learned by Variational Auto-Encoders

  A. Pește, L. Malagò, & S. Sârbu. (2017)

  In NIPS 2017 Workshop on Bayesian Deep Learning.
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• Finding patterns in visualizations of programs

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• Synthetic Generation of Local Minima and Saddle Points for Neural Networks

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  In ICML 2017 Workshop on Principled Approaches to Deep Learning.
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• Towards the Use of Gaussian Graphical Models in Variational Autoencoders

  A. Pește, & L. Malagò. (2017)

  In ICML 2017 Workshop on Implicit Models.
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• Hierarchical representations of perceptual and sensorimotor information in deep neural networks

  R. V. Florian. (2017)

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2016

• Chaos Control and Anticontrol of Complex Systems via Parrondo’s Game

  M. - F. Danca. (2016)

  In J. Lü, X. Yu, G. Chen, & W. Yu (Eds.), Complex Systems and Networks (p. 263–282)Berlin, Heidelberg: Springer Berlin Heidelberg.
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• Note on a parameter switching method for nonlinear ODEs

  M. - F. Danca, & M. Fečkan. (2016)

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• Hidden transient chaotic attractors of Rabinovich–Fabrikant system

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  Nonlinear Dynamics, 86(2), 1263–1270.
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• Spatial embedding and wiring cost constrain the functional layout of the cortical network of rodents and primates

  S. Horvát, R. Gămănuț, M. Ercsey-Ravasz, L. Magrou, B. Gămănuț, D. C. Van Essen, .... (2016)

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• Emulating “Chaos + Chaos = Order” in Chen’s Circuit of Fractional Order by Parameter Switching

  W. K. S. Tang, & M. - F. Danca. (2016)

  International Journal of Bifurcation and Chaos, 26(06), 1650096.
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• Chaos control of Hastings–Powell model by combining chaotic motions

  M. - F. Danca, & J. Chattopadhyay. (2016)

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• Hidden and Nonstandard Bifurcation Diagram of an Alternate Quadratic System

  G. Pastor, M. Romera, M. - F. Danca, A. Martin, A. B. Orue, F. Montoya, & L. H. Encinas. (2016)

  International Journal of Bifurcation and Chaos, 26(02), 1650036.
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• Looking More Closely at the Rabinovich–Fabrikant System

  M. - F. Danca, M. Fec̆kan, N. Kuznetsov, & G. Chen. (2016)

  International Journal of Bifurcation and Chaos, 26(02), 1650038.
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