2021

• Attractor as a convex combination of a set of attractors

  M. - F. Danca, M. Feckan, N. Kuznetsov, & G. Chen. (2021)

  Communications in Nonlinear Science and Numerical Simulation, 96, 105721.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Hidden and self-exited attractors in a heterogeneous Cournot oligopoly model

  M. - F. Danca, & M. Lampart. (2021)

  Chaos, Solitons & Fractals, 142, 110371.
  Full text (via DOI) · Google Scholar · Epistemio
• Modal Functional ('Dialectica') Interpretation

  D. Hernest, & T. Trifonov. (2021)

  arXiv:1212.0020.
  Google Scholar · Epistemio

2020

• Bifurcation and Chaos in Fractional- Order Systems

  Bifurcation and Chaos in Fractional- Order Systems. (2020)

  (M. - F. Danca & G. Chen, Eds.) Basel: MDPI.
  Google Scholar · Epistemio
• Puu system of fractional order and its chaos suppression

  M. - F. Danca. (2020)

  Symmetry, 12(3), 340.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Chaos suppression in a Gompertz-like discrete system of fractional order

  M. - F. Danca, & M. Feckan. (2020)

  International Journal of Bifurcation and Chaos, 30(3), 2050049.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Constraining the Reionization History using Bayesian Normalizing Flows

  H. Hortúa, L. Malagò, & R. Volpi. (2020)

  Machine Learning: Science and Technology, 1, 035014.
  Full text (via DOI) · Google Scholar · Epistemio
• Biharmonic δ(r)-ideal hypersurfaces in Euclidean spaces are minimal

  Deepika, & A. Arvanitoyeorgos. (2020)

  Differential Geometry and its Applications, 72.
  Full text (via DOI) · Google Scholar · Epistemio
• Early Pleistocene freshwater fishes of Copăceni (Dacian Basin, southern Romania)

  Ş. Vasile, O. Kovalchuk, A. Petculescu, & M. Venczel. (2020)

  Paleontologia Electronica.
  Full text (via DOI) · Google Scholar · Epistemio
• Management of water bodies in show caves – A microbial approach

  O. T. Moldovan, S. Bercea, R. Năstase-Bucur, S. Constantin, M. Kenesz, I. C. Mirea, .... (2020)

  Tourism Management, 78, 104037.
  Full text (via DOI) · Google Scholar · Epistemio
• An extension of the second order dynamical system that models Nesterov’s convex gradient method

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

  Applied Mathematics & Optimization.
  Full text (via DOI) · Google Scholar · Epistemio
• 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)

  Sensors, 20(11), 3032.
  Full text (via DOI) · Google Scholar · Epistemio
• New optimization algorithms for neural network training using operator splitting techniques

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

  Neural Networks, 126, 178-190.
  Full text (via DOI) · Google Scholar · Epistemio
• Automatic Feature Extraction for Phonocardiogram Heartbeat Anomaly Detection using WaveNet VAE

  R. - G. Colț, & C. - H. Várady. (2020)

  In Machine Learning for Healthcare and Pharma Applications ECML PKDD 2020 Workshop.
  Google Scholar · Epistemio
• Detection of Tumours in Brain MRIs with Variational AutoEncoders

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

  In Machine Learning for Healthcare and Pharma Applications ECML PKDD 2020 Workshop.
  Google Scholar · Epistemio
• Reliable Uncertainties for Bayesian Neural Networks using Alpha-divergences

  H. J. Hortúa, L. Malagò, & R. Volpi. (2020)

  In ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning.
  Google Scholar · Epistemio
• Evaluating Natural Alpha Embeddings on Intrinsic and Extrinsic Tasks

  R. Volpi, & L. Malagò. (2020)

  In 5th Workshop on Representation Learning for NLP .
  Google Scholar · Epistemio
• Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations

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

  In 2020 KDD Workshop on Applied Data Science for Healthcare.
  Google Scholar · Epistemio
• Parameters Estimation from the 21 cm signal using Variational Inference

  H. J. Hortúa, R. Volpi, & L. Malagò. (2020)

  In ICLR 2020 Fundamental Science in the era of AI .
  Google Scholar · Epistemio
• Performance evaluation of Graph Convolutional Networks with Siamese training for few-shot classification of nodes

  N. Uțiu. (2020)

  In Bridge between perception and reasoning: Graph neural networks and beyond - ICML 2020 workshop.
  Google Scholar · Epistemio
• 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.
  Full text (via DOI) · Google Scholar · Epistemio
• 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.
  Full text (via DOI) · Google Scholar · Epistemio
• Lagrangian and Hamiltonian Mechanics for Probabilities on the Statistical Manifold

  G. Chirco, L. Malagò, & G. Pistone. (2020)

  ArXivarXiv:2009.09431.
  Google Scholar · Epistemio
• Natural Wake-Sleep Algorithm

  C. Várady, R. Volpi, L. Malagò, & N. Ay. (2020)

  arXiv:2008.06687.
  Google Scholar · Epistemio
• Training highly effective connectivities within neural networks with randomly initialized, fixed weights

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

  arXiv:2006.16627.
  Google Scholar · Epistemio
• 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)

  arXiv:2001.10831.
  Google Scholar · Epistemio

2019

• Graphical structure of attraction basins of hidden attractors: the Rabinovich-Fabrikant system

  M. - F. Danca, P. Bourke, & N. Kuznetsov. (2019)

  International Journal of Bifurcation and Chaos, 29(1), 1930001.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Difference equations with impulses

  M. - F. Danca, & M. Feckan. (2019)

  Opuscula Mathematica, 39(1), 5-22.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Chaos control in the fractional order logistic map via impulses

  M. - F. Danca, M. Feckan, & N. Kuznetsov. (2019)

  Nonlinear Dynamics, 98(2), 1219–1230.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Rich dynamics and anticontrol of extinction in a prey-predator system

  M. - F. Danca, M. Feckan, N. Kuznetsov, & G. Chen. (2019)

  Nonlinear Dynamics, 98(2), 1421–1445.
  Full text (via DOI) · Google Scholar · Epistemio
• Hidden chaotic attractors and chaos suppression in an impulsive discrete economical supply and demand dynamical system

  M. - F. Danca, & M. Feckan. (2019)

  Communications in Nonlinear Science and Numerical Simulation, 74( ), 1-13.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• The Growth and Decline of the Western Roman Empire

  S. Roman, & E. Palmer. (2019)

  Cliodynamics, 10(2).
  Full text (via DOI) · Google Scholar · Epistemio
• 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)

  PLOS One, 14(10), e0223593.
  Full text (via DOI) · Google Scholar · Epistemio
• Deep Knowledge Based Agent: Learning to do tasks by self-thinking about imaginary worlds

  A. Davody. (2019)

  In Reinforcement Learning for Real Life ICML 2019 Workshop.
  Google Scholar · Epistemio
• Analyzing the theoretical grounds of curiosity-driven, intrinsically-motivated learning

  R. V. Florian. (2019)

  In The Fourth International Workshop on Intrinsically Motivated Open-ended Learning (IMOL 2019).
  Google Scholar · Epistemio
• Convolutional Neural Networks on Randomized Data

  C. Ivan. (2019)

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

  C. Ivan, & B. Indurkhya. (2019)

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

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

  arXiv:1911.08508.
  Google Scholar · Epistemio
• Natural Alpha Embeddings

  R. Volpi, & L. Malagò. (2019)

  arXiv:1912.02280.
  Google Scholar · Epistemio

2018

• Matlab code for Lyapunov exponents of fractional order systems

  M. - F. Danca, & N. Kuznetsov. (2018)

  International Journal of Bifurcation and Chaos, 28(5), 1850067.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Complex dynamics, hidden attractors and continuous approximation of a fractional-order hyperchaotic PWC system

  M. - F. Danca, M. Feckan, & G. Chen. (2018)

  Nonlinear Dynamics, 91(4), 2523–2540.
  Full text (via DOI) · Full text (PDF) · Google Scholar · Epistemio
• Wasserstein Riemannian geometry of Gaussian densities

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

  Information Geometry, 1(2), 137–179.
  Full text (via DOI) · Google Scholar · Epistemio
• A continuous-time MaxSAT solver with high analog performance

  B. Molnár, F. Molnár, M. Varga, & M. Ercsey-Ravasz. (2018)

  Nature Communications, 9, 4864.
  Full text (via DOI) · Google Scholar · Epistemio
• Approximating hidden chaotic attractors via parameter switching

  M. - F. Danca, N. Kuznetsov, & G. Chen. (2018)

  Chaos, 28, 013127.
  Full text (via DOI) · Google Scholar · Epistemio
• 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)

  Neuron, 97(3), 698-715.
  Full text (via DOI) · Google Scholar · Epistemio
• Generalization of the Filippov method for systems with large periodic input

  C. Morel, & M. - F. Danca. (2018)

  Mathematics and Computers in Simulation, 146, 1-13.
  Full text (via DOI) · Google Scholar · Epistemio
• Fractional-order PWC systems without zero Lyapunov exponents

  M. - F. Danca, N. Kuznetsov, & G. Chen. (2018)

  Nonlinear Dynamics, 92(3), 1061–1078.
  Full text (via DOI) · Google Scholar · Epistemio
• Lyapunov exponents of a hyperchaotic discontinuous 4D system of integer or fractional order

  M. - F. Danca. (2018)

  Entropy, 20, 337.
  Full text (via DOI) · Google Scholar · Epistemio
• Modeling cognitive processes underlying computer programming

  C. F. Perțicaș, & B. Indurkhya. (2018)

  In 29th Annual Workshop of the Psychology of Programming Interest Group - PPIG 2018 (p. 16-27).
  Google Scholar · Epistemio
• 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.
  Google Scholar · Epistemio

Powered by Epistemio Outcomes