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Borja Ibarz

As seen in: arXiv, The Astronomical Journal
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Articles

[2305.13233] Estimating Gibbs free energies via isobaric-isothermal flows

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By Borja Ibarz, George Papamakarios
| arXiv
arXiv:2305.13233 (physics) [Submitted on 22 May 2023 (v1), last revised 6 Sep 2023 (this version, v3)] Download PDF Comments: Subjects: Computational Physics (physics.comp-ph); Statistical Mechanics (cond-mat.stat-mech); Machine Learning (cs.LG); Machine Learning (stat.ML) Cite as: arXiv:2305.13233 [physics.comp-ph] (or arXiv:2305.13233v3 [physics.comp-ph] for this version) https://doi.org/10.48550/arXiv.2305.13233 Submission history From: George Papamakarios [ view email] [v1] Mon, 22 May...
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Machine Learning: Science and Technology

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By Peter Wirnsberger, George Papamakarios, Borja Ibarz, Sebastien Racaniere
| The Astronomical Journal Verified
Accurate estimation of equilibrium properties of a thermodynamic system is a central challenge of computational statistical mechanics [1, 2]. For decades, molecular dynamics (MD) and hybrid Monte Carlo [3] have been the methods of choice for sampling such systems at scale [4–6]. Recently there has been a surge in using deep learning to develop learned schemes for sampling from probability distributions in general and physical systems in particular, most notably using normalizing flows [7, 8].
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The Spatial Memory Pipeline: a model of egocentric to allocentric understanding in mammalian brains

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By Benigno Uria, Andrea Banino, Borja Ibarz, Vinicius Zambaldi
| BioRxiv
Abstract In the mammalian brain, allocentric representations support efficient self-location and flexible navigation. A number of distinct populations of these spatial responses have been identified but no unified function has been shown to account for their emergence. Here we developed a network, trained with a simple predictive objective, that was capable of mapping egocentric information into an allocentric spatial reference frame.
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