Registration

Yuhai Tu

IBM Watson Research Center

Stochastic learning dynamics and generalization in neural networks: A statistical physics approach for understanding deep learning

M. Ruiz-Garcia

Universidad Complutense de Madrid

Out-of-equilibrium machine learning: Dynamical loss functions and catastrophic forgetting

Soon Hoe Lim

Nordita, KTH Royal Institute of Technology and Stockholm University

Noisy Recurrent Neural Networks

Coffee break / Poster Session

Pankaj Mehta

Boston University

Why can we learn with so many parameters? The geometry and statistical physics of overparameterization

B. Requena

ICFO – Institut de Ciències Fotòniques,
The Barcelona Institute of Science and Technology

Inferring pointwise diffusion properties of single trajectories with deep learning

A. Bermades

Universidade Federal de Ouro Preto

ON THE FRACTAL PATTERNS OF LANGUAGE STRUCTURES

A. Chiatto

University of Naples Federico II

Training Circuit-based Quantum Classifiers through Memetic
Algorithms

H.J. Happen

Radbout Universiteit

Why adiabatic quantum annealing is unlikely to yield speed-up

P. Calvo-Barlés

Instituto de Nanociencia y Materiales de Aragón (INMA),
CSIC-Universidad de Zaragoza

Finding discrete symmetry groups via Deep Learning

Q. Yao

Columbia University

Inference of Disease Dispersion Rates of a Branching Model with Spatial and Temporal Information using GNN

Poster Session

G. Fernández-F

ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology

Extracting Relevant Physical Parameters from Stochastic Trajectories with Variational Autoencoders

P. Rosillo-Rodes

Institute for Cross-Disciplinary Physics and Complex Systems IFISC (UIB-CSIC)

Lexical differentiation of flamenco genres using machine learning

P. Korcyl

Institute of Applied Computer Science, Jagiellonian University

Mutual information in the Ising model from autoregressive neural networks

Ludovic Berthier

Université de Montpellier

Machine learning glasses

G. Valentini

University of Milan

An algorithmic framework for heterogeneous multigraph
embedding

A. Banerjee

Max Planck Institute for Polymer Research

Data-driven identification and analysis of the glass transition in polymer melts

Coffee break / Poster Session

Juan P. Garrahan

University of Nottingham

Trajectory ensembles and Machine Learning

J.J. Bermejo-Vega

Universidad de Granada

How to analyze hate networks in social media with machine
learning and statistical physics

A. Prat Pou

Universitat Politècnica de Catalunya

Efficient Evaluation of the Partition Function of Restricted Boltzmann Machines with Annealed Importance Sampling

D. Valle

Universidad Rey Juan Carlos

Deep Learning-based Analysis of Basins of Attraction

G. Barrios

Universidad de Granada

Optimal representations in neural systems at the edge of chaos

Adi Makmal

Institute for Theoretical Physics
University of Innsbruck

Qubit-efficient variational quantum algorithms

Gilhan Kim

Seoul National University

Tradeoff in Unsupervised Learning: Interplay of Model Error and Data Error

P. Villegas

Centro Ricerche Enrico Fermi

Laplacian Renormalization Group: A ’zoom lens’ for networks

Poster Session

J.M. Tucny

Università degli Studi Roma Tre

Learning of viscosity functions in rarefied gas flows with
physics-informed neural networks

A. Doliwa

University of Warmia and Mazury

SPECTRAL QUANTIZATION OF DISCRETE RANDOM WALKS ON HALF-LINE, AND ORTHOGONAL POLYNOMIALS ON THE UNIT CIRCLE

L. Valkunas

Vilnius University

Femtosecond and picosecond excitation dynamics in FCP
complexes: results from 2D spectroscopy and streak-camera measurements

K. Birgitta Whaley

University of California (Berkeley)

Interplay between machine learning and quantum computing

D. Manzano

Universidad de Granada

Autonomous Approach for Quantum Entanglement Detection and
Classification Using Multi-Layer Perceptrons

A. Sannia

Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) UIB-CSIC

Engineered dissipation to mitigate barren plateaus

Coffee break / Poster Session

G.G. Guerreschi

Intel

Realization of quantum neural networks using repeat-until-success circuits

S. Roca-Jerat

Instituto de Nanociencia y Materiales de Aragón (CSIC – Universidad de Zaragoza)

QUANTUM MACHINE LEARNING WITH QUDITS

V. Kuzmin

Institute for Theoretical Physics

Optimizing Variational Quantum Circuits using Gaussian Process Surrogate Modeling with Trigonometric Kernels

G. Escrig Mas

Universidad Complutense de Madrid

Parameter estimation of gravitational waves with a quantum
metropolis algorithm

D. Rose

University College London

Reinforcement learning for rare trajectories in stochastic systems

V. Martín Mayor

Universidad Complutense de Madrid

Quantum spin glasses on the GPU

A. Ferrer-Sánchez

University of Valencia

Gradient-Annihilated PINNs for Solving Riemann Problems:
Application to Relativistic Hydrodynamics

J. Borondo

Universidad Pontificia de Comillas

Anticipating food price crises by reservoir computing and
quantum reservoir computing

Poster Session

P. Lipka-Bartosik

University of Geneva

Thermal Neuron: Computation via Heat Flows

I. Fernández-Iriondo

University of the Basque Country

Brain Mapping of Behavioral Domains Using Multi-Scale
Networks and Canonical Correlation Analysis

J. García Condado

Biocurcs-Bizkaia HRI, UPV/EHU

NeuropsychBrainAge: a biomarker for conversion from mild
cognitive impairment to Alzheimer’s disease

Visit Albaycin & Sacromonte

Gala Dinner

Seth Lloyd

MIT

Advances in quantum machine learning

R. Campos

Universidad Complutense de Madrid

Quantum Metropolis Solver: A Quantum Walks Approach to
Optimization Problems

M. Krumm

University of Innsbruck

Reinforcement learning via single-photon quantum walks, and perspectives on explainable quantum machine learning

Coffee break / Poster Session

Lucas Lamata

Universidad de Sevilla

Quantum Reinforcement Learning with Quantum Technologies

J.J. Torres

Universidad de Granada

Building a Quantum Synapse Paradigm

Y. Kuriatnikov

TU WIEN ATOMINSTITUT

OPTIMIZING OPTICAL POTENTIALS WITH
PHYSICS-INSPIRED LEARNING ALGORITHMS

M. Garcia de Andoin

University of the Basque Country UPV/EHU

HYBRID QUANTUM-CLASSICAL SEARCH SPACE REDUCTION HEURISTIC FOR OPTIMIZATION

M. Skotiniotis

Universidad de Granada

Universal algorithms for quantum data learning

Farewell