Publications related to Local invertibility and sensitivity of atomic structure-feature mappings

Related publications (38)

Integrating Neural Interfaces with Machine Learning: Enabling Self-Sufficient and Ubiquitous Prosthetic and Diagnostic Devices

Mahsa Shoaran, Mohammad Ali Shaeri, Jinhan Liu

Advanced neural interfaces are transforming applications ranging from neuroscience research to diagnostic tools (for mental state recognition, tremor and seizure detection) as well as prosthetic devices (for motor and communication recovery). By integratin ...

IEEE2025

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

'Fraternal-twin' ferroelectricity: competing polar states in hydrogen-doped samarium nickelate from first principles

Michele Kotiuga

In ferroelectric switching, an applied electric field switches the system between two polar symmetry-equivalent states. In this work, we use first-principles calculations to explore the polar states of hydrogen-doped samarium nickelate (SNO) at a concentra ...

Iop Publishing Ltd2024

Band Gap Renormalization at Different Symmetry Points in Perovskites

Majed Chergui, Lijie Wang

Using ultrafast broad-band transient absorption (TA) spectroscopy of photoexcited MAPbBr3 thin films with probe continua in the visible and the mid- to deep-ultraviolet (UV) ranges, we capture the ultrafast renormalization at the fundamental gap at the R s ...

Amer Chemical Soc2024

Mean value theorems for collections of lattices with a prescribed group of symmetries

Nihar Prakash Gargava

Euclidean lattices are mathematical objects of increasing interest in the fields of cryptography and error-correcting codes. This doctoral thesis is a study on high-dimensional lattices with the motivation to understand how efficient they are in terms of b ...

EPFL2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Development of End-to-End Artificial Intelligence Models for Surgical Planning in Transforaminal Lumbar Interbody Fusion

Minh Hieu Lê

Transforaminal lumbar interbody fusion (TLIF) is a commonly used technique for treating lumbar degenerative diseases. In this study, we developed a fully computer-supported pipeline to predict both the cage height and the degree of lumbar lordosis subtract ...

2024

Randomized flexible GMRES with deflated restarting

Laura Grigori

For a high-dimensional problem, a randomized Gram-Schmidt (RGS) algorithm is beneficial in terms of both computational cost and numerical stability. We apply this dimension reduction technique by random sketching to Krylov subspace methods, e.g., to the ge ...

Springer2024

CONTROL OF HYPERBOLIC AND PARABOLIC EQUATIONS ON NETWORKS AND SINGULAR LIMITS

Nicola De Nitti

vanishing viscosity, networks. This work has received funding from the Alexander von Humboldt-Professorship program, the Transregio 154 Project "Mathematical Modelling, Simulation and Optimization Using the Example of Gas Networks" of the DFG, the grant PI ...

Amer Inst Mathematical Sciences-Aims2024

Topics in statistical physics of high-dimensional machine learning

Hugo Chao Cui

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

EPFL2024

On the selection and effectiveness of pseudo-absences for species distribution modeling with deep learning

Devis Tuia, Benjamin Alexander Kellenberger, Nina Marion Aurélia Van Tiel, Lloyd Haydn Hughes, Robin Adrien Zbinden

Species distribution modeling is a highly versatile tool for understanding the intricate relationship between environmental conditions and species occurrences. However, the available data often lacks information on confirmed species absence and is limited ...

Elsevier2024

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

Dynamic nuclear polarisation of 1H in Gd-doped In(OH)3

David Lyndon Emsley, Michael Allan Hope, Amrit Venkatesh, Yuxuan Zhang

Dynamic nuclear polarisation (DNP) of solids doped with high-spin metal ions, such as Gd3+, is a useful strategy to enhance the nuclear magnetic resonance (NMR) sensitivity for these samples. Spin diffusion can relay polarisation throughout a sample, which ...

Academic Press Inc - Elsevier Science2023

Polarization-Controlled Chromo-Encryption

Olivier Martin, Hsiang-Chu Wang

The response of simple plasmonic nanorods to polarized illumination is studied in detail. Depending on the orientation of that polarization with respect to the symmetry axes of the nanostructure, a chiral response can occur, which can be analyzed through a ...

WILEY-V C H VERLAG GMBH2023

Symmetry-Induced Singlet-Triplet Inversions in Non-Alternant Hydrocarbons

Anne-Clémence Corminboeuf, Jacob Terence Blaskovits, Marc Hamilton Folkmann Garner

Molecules with inversion of the singlet and triplet excited-state energies are highly promising for the development of organic light-emitting diodes (OLEDs). To date, azaphenalenes are the only class of molecules where these inversions have been identified ...

Wiley-VCH Verlag GmbH2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

Critical line of the triangular Ising antiferromagnet in a field from a C3-symmetric corner transfer matrix algorithm

Afonso Dos Santos Rufino, Frédéric Mila, Jeanne Colbois, Samuel Louis Nyckees

The corner transfer matrix renormalization group (CTMRG) algorithm has been extensively used to investigate both classical and quantum two-dimensional (2D) lattice models. The convergence of the algorithm can strongly vary from model to model depending on ...

Amer Physical Soc2023

Exact quantum conformal symmetry, its spontaneous breakdown, and gravitational Weyl anomaly

Mikhail Chapochnikov, Anna Tokareva

The classical Lagrangian of the Standard Model enjoys the symmetry of the full conformal group if the mass of the Higgs boson is put to zero. This is a hint that conformal symmetry may play a fundamental role in the ultimate theory describing nature. The o ...

American Physical Society2023

On A Special Symmetry In The Dynamics Of Complex Systems In A Holographic-Type Perspective

Maria-Alexandra Paun

By operating with the Scale Relativity Theory in the dynamics of complex systems, we can achieve a description of these complex systems through a holographic-type perspective. Then, gauge invariances of a Riccati-type become functional in complex system dy ...

UNIV POLITEHNICA BUCHAREST, SCI BULL2023

Correspondence functors and duality

Jacques Thévenaz, Serge Bouc

A correspondence functor is a functor from the category of finite sets and correspondences to the category of k-modules, where k is a commutative ring. By means of a suitably defined duality, new correspondence functors are constructed, having remarkable p ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023