Estelle Maeva Inack

Estelle Maeva Inack profile picture
Research Scientist
Perimeter Institute for Theoretical Physics
Research Associate
Areas of research:
Quantum Matter
(519) 569-7600 x5014
Machine learning, quantum computing, quantum Monte Carlo
  • 2020 - 2022 Vector Institute, Postgraduate affiliate
  • E. M. Inack, S. Morawetz and R. G. Melko, "Neural Annealing and Visualization of Autoregressive Neural Networks in the Newman-Moore Model" Condens. Matter 2022, 7, 38.
  • M. Hibat-Allah, E. M. Inack, R. Wiersema, R. G. Melko, J. Carrasquilla, "Variational Neural Annealing" Nature Machine Intelligence volume 3, pages 952-961 (2021)
  • T. Parolini, E. M. Inack, G. Giudici, and S. Pilati "Tunneling in projective quantum Monte Carlo simulations with guiding wave functions" Phys. Rev. B 100, 214303 (2019)
  • S. Pilati, E. M. Inack, P. Pieri "Self-learning projective quantum Monte Carlo simulations guided by restricted Boltzmann machines" Phys. Rev. E 100, 043301 (2019)
  • E. M. Inack, G. E. Santoro, L. Dell'Anna, and S. Pilati "Projective quantum Monte Carlo simulations guided by unrestricted neural network states" Phys. Rev. B 98, 235145 (2018)
  • E. M. Inack, G. Giudici, T. Parolini, G. Santoro, and S. Pilati "Understanding quantum tunneling using diffusion Monte Carlo simulations" Phys. Rev. A 97, 032307 (2018)
  • E. M. Inack and S. Pilati "Simulated quantum annealing of double-well and multiwell potentials" Phys. Rev. E 92, 053304 (2015)
  • F. M. Moukam Kakmeni, E. M. Inack, and E. M. Yamakou "Localized nonlinear excitations in diffusive Hindmarsh-Rose neural networks" Phys. Rev. E 89, 052919 (2014)
  • E. M. Yamakou, E. M. Inack, "Coherence resonance and stochastic synchronization in a small-world neural network: An interplay in the presence of spike-timing-dependent plasticity", arXiv: 2201.054366 (2022)
  • "Variational neural simulations and annealing", Amazon Quantum Computing
  • "L"informatique quantique, qu"es-ce que c"est, et pourquoi s"y intéresser?", University of Yaoundé I
  • "Neural annealing and visualization of autoregressive neural networks in the Newman-Moore model", Machine Learning Augmented Sampling for the Molecular Sciences, EPFL
  • "When a Quantum Physicist meets Artificial Intelligence", AIMS Cameroon
  • "Variational Neural Annealing", McGill University
  • "Variational Neural Annealing", XXXII IUPAP Conference on Computational Physics
  • "Variational Quantum Annealing Simulations of Non-stoquastic Hamiltonians", Adiabatic Quantum Computing Virtual Conference
  • "Variational Quantum Annealing Simulations of Non-stoquastic Hamiltonians", APS March Meetings
  • "Variational Neural Annealing", Machine Learning and the Physical Sciences Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS)
  • "Variational Neural Annealing", University of Erlangen-Nürnberg
  • "Variational Neural Annealing", African Physical Society (AfPS) International Conference
  • "Variational Neural Annealing", Quantum Techniques in Machine Learning
  • "Variational Neural simulations and annealing", Okinawa Institute of Science and Technology
  • "Variational Monte Carlo", Universidad di Los Andes
  • "VMC and Machine learning", KITP
  • PIRSA:22050040, Neural annealing and visualization of autoregressive neural networks, 2022-05-18, Quantum Criticality: Gauge Fields and Matter
  • PIRSA:18100093, Simulating quantum annealing via projective quantum Monte Carlo algorithms, 2018-10-26, Machine Learning Initiative